From 640ce45d0e9233eb0785c0174a399448f7b8ec37 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Thu, 17 Sep 2026 14:10:47 +0200 Subject: [PATCH 01/16] perf(color): extract centroids from the used palette --- vectorizing/solvers/color/quantize.py | 23 +++---- vectorizing/tests/test.py | 98 +++++++++++++++++++++++++++ 2 files changed, 108 insertions(+), 13 deletions(-) diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index 8949803..8851ace 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -145,23 +145,20 @@ def write_background_cluster(labels, bg_cluster): labels = np.where(bg_cluster > 0, 0, labels) return labels -# Gets initial centroids for kmeans clustering -# by quantizing an image using FASTOCTREE method -def get_initial_centroids(img_arr, color_count): + +def get_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: + """Return sorted unique used RGB palette colors for K-means initialization.""" img = Image.fromarray(img_arr) - img = img.quantize( - color_count, - method = Image.Quantize.FASTOCTREE - ).convert('RGB') + img = img.quantize(color_count, method=Image.Quantize.FASTOCTREE) - img_arr = np.asarray(img) - channel_count = img_arr.shape[-1] + # Ignore unused entries: palette padding must not add extra K-means clusters. + # Keep np.unique's RGB order and deduplication, but sort only the used palette + # rather than every pixel. Centroid order affects K-means results. + used_indices = [index for _, index in img.getcolors()] + palette = np.asarray(img.getpalette("RGB"), dtype=np.uint8).reshape(-1, 3) + return np.unique(palette[used_indices], axis=0) - return np.unique( - np.reshape(img_arr, (-1, channel_count)), - axis = 0 - ).astype(np.uint8) def kmeans(img_arr, init_centroids): channel_count = img_arr.shape[-1] diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py index 03d6636..c42012b 100644 --- a/vectorizing/tests/test.py +++ b/vectorizing/tests/test.py @@ -7,8 +7,10 @@ from cairosvg import svg2png from PIL import Image +from vectorizing.geometry.bounds import compound_paths_bounds from vectorizing.server.s3 import get_s3_client from vectorizing.server.timer import Timer +from vectorizing.solvers.color import quantize as color_quantize from vectorizing.solvers.color.ColorSolver import ColorSolver from vectorizing.svg.markup import generate_SVG_markup from vectorizing.tests import testutil @@ -161,6 +163,102 @@ def test_color_solver_preserves_empty_transparent_image(): assert rendered.getchannel("A").getextrema() == (0, 0) +def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: + """Freeze the original RGB-pixel algorithm as an independent regression oracle.""" + img = ( + Image.fromarray(img_arr) + .quantize(color_count, method=Image.Quantize.FASTOCTREE) + .convert("RGB") + ) + pixels = np.asarray(img) + return np.unique(pixels.reshape(-1, pixels.shape[-1]), axis=0).astype(np.uint8) + + +@pytest.mark.parametrize("color_count", [2, 6, 16, 64]) +@pytest.mark.parametrize("seed", range(5)) +def test_initial_centroids_match_original(color_count: int, seed: int) -> None: + """Preserve exact dtype, values and ordering on random and sparse RGB inputs.""" + rng = np.random.default_rng(seed) + noise = rng.integers(0, 256, size=(63, 67, 3), dtype=np.uint8) + for pixels in ( + noise, + noise[::2, ::2], # Non-contiguous input. + noise[:1, :1], # Only one used palette entry. + np.full_like(noise, (175, 80, 230)), # Unused black entries must be ignored. + (noise // 128) * 128, # Fewer distinct colors than some requests. + ): + expected = legacy_initial_centroids(pixels, color_count) + actual = color_quantize.get_initial_centroids(pixels, color_count) + np.testing.assert_equal(actual.dtype, expected.dtype) + np.testing.assert_equal(actual.dtype, np.dtype(np.uint8)) + np.testing.assert_array_equal(actual, expected) + + +def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep only used RGB colors, deduplicated and sorted rather than palette order.""" + indexed = Image.new("P", (3, 1)) + indexed.putdata([7, 3, 5]) + palette = np.zeros((256, 3), dtype=np.uint8) + palette[1] = (255, 0, 0) # Unused nonblack entry. + palette[3] = palette[7] = (90, 10, 20) # Duplicate used RGB entries. + palette[5] = (10, 20, 30) + indexed.putpalette(palette.ravel().tolist()) + with monkeypatch.context() as patch: + patch.setattr(Image.Image, "quantize", lambda *args, **kwargs: indexed) + pixels = np.zeros((1, 3, 3), dtype=np.uint8) + actual = color_quantize.get_initial_centroids(pixels, 64) + expected = legacy_initial_centroids(pixels, 64) + np.testing.assert_array_equal(actual, expected) + np.testing.assert_array_equal(actual, [[10, 20, 30], [90, 10, 20]]) + + +@pytest.mark.parametrize( + "image_name, color_count", + [ + ("bubbles.png", 5), + ("shapes_2.png", 7), + ("aftermath.png", 2), + ("aftermath.png", 6), + ("aftermath.png", 16), + ("aftermath.png", 64), + ("empty.png", 6), + ("1px.jpg", 9), + ], +) +def test_centroid_optimization_preserves_vectorization( + image_name: str, + color_count: int, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Compare final SVG, colors, dimensions and bounds against the old algorithm.""" + with Image.open(Path(__file__).parent / "images" / image_name) as image: + actual = ColorSolver(image, color_count, Timer()).solve() + monkeypatch.setattr( + color_quantize, + "get_initial_centroids", + legacy_initial_centroids, + ) + expected = ColorSolver(image, color_count, Timer()).solve() + + actual_paths, actual_colors, actual_width, actual_height = actual + expected_paths, expected_colors, expected_width, expected_height = expected + np.testing.assert_array_equal(actual_colors, expected_colors) + np.testing.assert_equal( + (actual_width, actual_height), + (expected_width, expected_height), + ) + np.testing.assert_equal( + compound_paths_bounds(actual_paths), + compound_paths_bounds(expected_paths), + ) + # Byte-identical SVG is stricter than a raster tolerance and includes transparency. + np.testing.assert_equal( + generate_SVG_markup(*actual), generate_SVG_markup(*expected) + ) + + def test_uploads_markup_to_s3(client): response = client.post( "/", From 095da2388c976a838e5741c0846a712e28360458 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Thu, 17 Sep 2026 15:19:07 +0200 Subject: [PATCH 02/16] style(tests): satisfy trailing-comma hook --- vectorizing/tests/test.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py index c42012b..229bf83 100644 --- a/vectorizing/tests/test.py +++ b/vectorizing/tests/test.py @@ -255,7 +255,8 @@ def test_centroid_optimization_preserves_vectorization( ) # Byte-identical SVG is stricter than a raster tolerance and includes transparency. np.testing.assert_equal( - generate_SVG_markup(*actual), generate_SVG_markup(*expected) + generate_SVG_markup(*actual), + generate_SVG_markup(*expected), ) From f69c69bb7e0e7745e05fe94d38175134193dd123 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Thu, 17 Sep 2026 17:27:03 +0200 Subject: [PATCH 03/16] Merge pull request #73 from Kittl/perf/cumulative-bitmap-layering perf(color): build overlapping bitmaps with reverse sums --- vectorizing/solvers/color/bitmaps.py | 46 ++++---- vectorizing/solvers/color/quantize.py | 1 + vectorizing/tests/test.py | 159 +++++++++++++++++++++++--- 3 files changed, 164 insertions(+), 42 deletions(-) diff --git a/vectorizing/solvers/color/bitmaps.py b/vectorizing/solvers/color/bitmaps.py index bac0c11..1323d1d 100644 --- a/vectorizing/solvers/color/bitmaps.py +++ b/vectorizing/solvers/color/bitmaps.py @@ -1,28 +1,28 @@ -import numpy as np - -def create_bitmaps(labels, colors, has_background): - - bitmaps = [ - np.where(labels == label, 1, 0).astype(np.uint32) - for label in range(len(colors)) - ] +"""Build overlapping color masks for Potrace tracing.""" - if has_background: - bitmaps = bitmaps[1 : len(bitmaps)] - colors = colors[1 : len(colors)] +import numpy as np - zipped = list(zip(bitmaps, colors)) - # Empty bitmaps should be ignored - zipped = [[bitmap, color] for bitmap, color in zipped if np.sum(bitmap) > 0] - bitmaps = [bitmap for bitmap, _ in zipped] - colors = [color for _, color in zipped] +def create_bitmaps( + labels: np.ndarray, + colors: np.ndarray, + has_background: bool, +) -> tuple[list[np.ndarray], list[np.ndarray]]: + """Return cumulative uint32 masks and their colors in the original palette order.""" + bitmaps = [] + retained_colors = [] + for index, color in enumerate(colors): + if has_background and index == 0: + continue + mask = labels == index + # Pruned colors need no uint32 allocation; keep retained colors aligned. + if mask.any(): + bitmaps.append(mask.astype(np.uint32)) + retained_colors.append(color) - # Layer bitmaps so that holes are not produced after tracing - for x in range(len(bitmaps)): - bitmap_x = bitmaps[x] - for y in range(x + 1, len(bitmaps)): - bitmap_x += bitmaps[y] - bitmaps[x] = bitmap_x + # Work backwards: the next bitmap already contains every later layer. + # Preserve overlap to avoid tracing seams, with O(K*N) rather than O(K^2*N) work. + for index in range(len(bitmaps) - 2, -1, -1): + bitmaps[index] += bitmaps[index + 1] - return bitmaps, colors \ No newline at end of file + return bitmaps, retained_colors diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index 8851ace..a3bd234 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -155,6 +155,7 @@ def get_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: # Ignore unused entries: palette padding must not add extra K-means clusters. # Keep np.unique's RGB order and deduplication, but sort only the used palette # rather than every pixel. Centroid order affects K-means results. + # quantize() returns mode P: at most 256 entries, within getcolors()'s cap. used_indices = [index for _, index in img.getcolors()] palette = np.asarray(img.getpalette("RGB"), dtype=np.uint8).reshape(-1, 3) return np.unique(palette[used_indices], axis=0) diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py index 229bf83..d1ab1ef 100644 --- a/vectorizing/tests/test.py +++ b/vectorizing/tests/test.py @@ -1,6 +1,7 @@ import os from io import BytesIO from pathlib import Path +from unittest.mock import Mock import numpy as np import pytest @@ -11,6 +12,7 @@ from vectorizing.server.s3 import get_s3_client from vectorizing.server.timer import Timer from vectorizing.solvers.color import quantize as color_quantize +from vectorizing.solvers.color.bitmaps import create_bitmaps from vectorizing.solvers.color.ColorSolver import ColorSolver from vectorizing.svg.markup import generate_SVG_markup from vectorizing.tests import testutil @@ -174,24 +176,32 @@ def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarra return np.unique(pixels.reshape(-1, pixels.shape[-1]), axis=0).astype(np.uint8) +@pytest.mark.parametrize( + "variant", + ["noise", "strided", "one-pixel", "solid", "sparse"], +) @pytest.mark.parametrize("color_count", [2, 6, 16, 64]) @pytest.mark.parametrize("seed", range(5)) -def test_initial_centroids_match_original(color_count: int, seed: int) -> None: +def test_initial_centroids_match_original( + color_count: int, + seed: int, + variant: str, +) -> None: """Preserve exact dtype, values and ordering on random and sparse RGB inputs.""" rng = np.random.default_rng(seed) noise = rng.integers(0, 256, size=(63, 67, 3), dtype=np.uint8) - for pixels in ( - noise, - noise[::2, ::2], # Non-contiguous input. - noise[:1, :1], # Only one used palette entry. - np.full_like(noise, (175, 80, 230)), # Unused black entries must be ignored. - (noise // 128) * 128, # Fewer distinct colors than some requests. - ): - expected = legacy_initial_centroids(pixels, color_count) - actual = color_quantize.get_initial_centroids(pixels, color_count) - np.testing.assert_equal(actual.dtype, expected.dtype) - np.testing.assert_equal(actual.dtype, np.dtype(np.uint8)) - np.testing.assert_array_equal(actual, expected) + pixels = { + "noise": noise, + "strided": noise[::2, ::2], + "one-pixel": noise[:1, :1], + "solid": np.full_like(noise, (175, 80, 230)), # Ignore unused black entries. + "sparse": (noise // 128) * 128, + }[variant] + expected = legacy_initial_centroids(pixels, color_count) + actual = color_quantize.get_initial_centroids(pixels, color_count) + np.testing.assert_equal(actual.dtype, expected.dtype) + np.testing.assert_equal(actual.dtype, np.dtype(np.uint8)) + np.testing.assert_array_equal(actual, expected) def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( @@ -214,6 +224,107 @@ def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( np.testing.assert_array_equal(actual, [[10, 20, 30], [90, 10, 20]]) +def legacy_create_bitmaps( + labels: np.ndarray, + colors: np.ndarray, + has_background: bool, +) -> tuple[list[np.ndarray], list[np.ndarray]]: + """Freeze the original pairwise accumulation as an independent regression oracle.""" + bitmaps = [ + np.where(labels == index, 1, 0).astype(np.uint32) + for index in range(len(colors)) + ] + if has_background: + bitmaps = bitmaps[1:] + colors = colors[1:] + zipped = list(zip(bitmaps, colors)) + zipped = [[bitmap, color] for bitmap, color in zipped if np.sum(bitmap) > 0] + bitmaps = [bitmap for bitmap, _ in zipped] + colors = [color for _, color in zipped] + for x in range(len(bitmaps)): + bitmap_x = bitmaps[x] + for y in range(x + 1, len(bitmaps)): + bitmap_x += bitmaps[y] + bitmaps[x] = bitmap_x + return bitmaps, colors + + +@pytest.mark.parametrize( + "variant", + ["noise", "strided", "one-row", "one-column", "solid", "background", "sparse"], +) +@pytest.mark.parametrize("color_count", [1, 2, 6, 16, 64, 65]) +@pytest.mark.parametrize("has_background", [False, True]) +@pytest.mark.parametrize("seed", range(3)) +def test_bitmap_layering_matches_original( + color_count: int, + has_background: bool, + seed: int, + variant: str, +) -> None: + """Preserve masks, dtype, color order and read-only inputs across label patterns.""" + rng = np.random.default_rng(seed) + noise = rng.integers(0, color_count, size=(19, 23), dtype=np.uint16) + colors = rng.integers(0, 256, size=(color_count, 4), dtype=np.uint8) + colors.setflags(write=False) + labels = { + "noise": noise, + "strided": noise[::2, ::2], + "one-row": noise[:1, :], + "one-column": noise[:, :1], + "solid": np.full_like(noise, color_count - 1), + "background": np.zeros_like(noise), + "sparse": noise % 2, + }[variant] + labels.setflags(write=False) + expected_bitmaps, expected_colors = legacy_create_bitmaps( + labels, + colors, + has_background, + ) + actual_bitmaps, actual_colors = create_bitmaps(labels, colors, has_background) + np.testing.assert_array_equal(actual_colors, expected_colors) + np.testing.assert_equal(len(actual_bitmaps), len(expected_bitmaps)) + for actual, expected in zip(actual_bitmaps, expected_bitmaps): + np.testing.assert_equal(actual.dtype, np.dtype(np.uint32)) + np.testing.assert_array_equal(actual, expected) + + +@pytest.mark.parametrize("has_background", [False, True]) +@pytest.mark.parametrize("color_count", [0, 1, 6]) +def test_bitmap_layering_handles_empty_inputs( + has_background: bool, + color_count: int, +) -> None: + """Return no layers for empty labels or an empty palette.""" + colors = np.zeros((color_count, 3), dtype=np.uint8) + labels = np.empty((0, 3), dtype=np.uint8) + np.testing.assert_equal(create_bitmaps(labels, colors, has_background), ([], [])) + np.testing.assert_equal( + create_bitmaps(np.zeros((2, 2), dtype=np.uint8), colors[:0], has_background), + ([], []), + ) + + +def test_bitmap_layering_preserves_overlap_and_transparency() -> None: + """Keep suffix unions in palette order without including transparent pixels.""" + labels = np.array([[0, 1, 3, 4]], dtype=np.uint8) + colors = np.arange(20, dtype=np.uint8).reshape(5, 4) + # Label zero is transparent; label two is unused between visible layers. + bitmaps, visible_colors = create_bitmaps(labels, colors, True) + expected = np.array( + [[[0, 1, 1, 1]], [[0, 0, 1, 1]], [[0, 0, 0, 1]]], + dtype=np.uint32, + ) + np.testing.assert_array_equal(bitmaps, expected) + np.testing.assert_array_equal(visible_colors, colors[[1, 3, 4]]) + # The in-place accumulation must not make different layers share storage. + bitmaps[0][0, 0] = 1 + np.testing.assert_array_equal(bitmaps[1:], expected[1:]) + np.testing.assert_array_equal(labels, [[0, 1, 3, 4]]) + + +@pytest.mark.parametrize("optimization", ["centroids", "bitmaps"]) @pytest.mark.parametrize( "image_name, color_count", [ @@ -227,20 +338,30 @@ def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( ("1px.jpg", 9), ], ) -def test_centroid_optimization_preserves_vectorization( +def test_color_optimizations_preserve_vectorization( image_name: str, color_count: int, + optimization: str, monkeypatch: pytest.MonkeyPatch, ) -> None: """Compare final SVG, colors, dimensions and bounds against the old algorithm.""" with Image.open(Path(__file__).parent / "images" / image_name) as image: actual = ColorSolver(image, color_count, Timer()).solve() - monkeypatch.setattr( - color_quantize, - "get_initial_centroids", - legacy_initial_centroids, - ) + target, legacy = { + "centroids": ( + "vectorizing.solvers.color.quantize.get_initial_centroids", + legacy_initial_centroids, + ), + "bitmaps": ( + "vectorizing.solvers.color.ColorSolver.create_bitmaps", + legacy_create_bitmaps, + ), + }[optimization] + # Patch each lookup site and verify the legacy implementation was used. + reference = Mock(wraps=legacy) + monkeypatch.setattr(target, reference) expected = ColorSolver(image, color_count, Timer()).solve() + reference.assert_called_once() actual_paths, actual_colors, actual_width, actual_height = actual expected_paths, expected_colors, expected_width, expected_height = expected From f074fa542395d5f5769784e59250c2a8a8e75356 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 11:03:23 +0200 Subject: [PATCH 04/16] revert(color): restore pre-69 layer clipping (#75) * fix(color): restore editable cutouts between color layers * docs(color): describe clipping behavior without change history --- docker-compose.yml | 2 +- pytest.ini | 3 +- vectorizing/solvers/color/ColorSolver.py | 8 +-- vectorizing/solvers/color/clip.py | 67 ++++++++++++++++++++ vectorizing/tests/test.py | 62 ------------------ vectorizing/tests/test_color_layers.py | 81 ++++++++++++++++++++++++ 6 files changed, 155 insertions(+), 68 deletions(-) create mode 100644 vectorizing/solvers/color/clip.py create mode 100644 vectorizing/tests/test_color_layers.py diff --git a/docker-compose.yml b/docker-compose.yml index f5ee802..9389ea5 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -57,4 +57,4 @@ services: depends_on: moto-init: condition: service_completed_successfully - command: python -m pytest vectorizing/tests/test.py + command: python -m pytest vectorizing/tests diff --git a/pytest.ini b/pytest.ini index 03f586d..7a166d7 100644 --- a/pytest.ini +++ b/pytest.ini @@ -1,2 +1,3 @@ [pytest] -pythonpath = . \ No newline at end of file +pythonpath = . +python_files = test.py test_*.py *_test.py \ No newline at end of file diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index 97806b5..5d3fbe5 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -1,8 +1,8 @@ import numpy as np import potrace -from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.solvers.color.bitmaps import create_bitmaps +from vectorizing.solvers.color.clip import remove_layering from vectorizing.solvers.color.quantize import quantize from vectorizing.util.limit_size import limit_size @@ -34,9 +34,9 @@ def solve(self): traced_bitmaps = [potrace.Bitmap(bitmap).trace() for bitmap in bitmaps] self.timer.end_timer() - compound_paths = [ - potrace_path_to_compound_path(traced) for traced in traced_bitmaps - ] + self.timer.start_timer("Polygon Clipping") + compound_paths = remove_layering(traced_bitmaps, self.img, has_background) + self.timer.end_timer() return [compound_paths, colors, self.img.size[0], self.img.size[1]] diff --git a/vectorizing/solvers/color/clip.py b/vectorizing/solvers/color/clip.py new file mode 100644 index 0000000..0520d7b --- /dev/null +++ b/vectorizing/solvers/color/clip.py @@ -0,0 +1,67 @@ +"""Cut overlapping color paths into separate regions.""" + +import potrace +from pathops import Path, PathOp, PathOpsError, op +from PIL import Image + +from vectorizing.geometry.potrace import potrace_path_to_compound_path + + +def create_background_rect(img: Image.Image, padding: int) -> Path: + """Return the image rectangle expanded by padding on every side.""" + rect = Path() + rect.moveTo(-padding, -padding) + rect.lineTo(img.width + padding, -padding) + rect.lineTo(img.width + padding, img.height + padding) + rect.lineTo(-padding, img.height + padding) + rect.close() + return rect + + +def remove_layering( + traced_bitmaps: list[potrace.Path], + img: Image.Image, + has_background: bool, +) -> list[Path]: + """Subtract later colors from lower layers, retaining overlap if clipping fails.""" + compound_paths = [ + potrace_path_to_compound_path(traced) for traced in traced_bitmaps + ] + if has_background: + for index in range(len(compound_paths) - 1): + try: + compound_paths[index] = op( + compound_paths[index], + compound_paths[index + 1], + PathOp.DIFFERENCE, + ) + except PathOpsError: + break + return compound_paths + + disjoint_paths = [] + for index in range(len(compound_paths) - 1): + # Different padding keeps the rectangles' outer edges from coinciding. + base = create_background_rect(img, (index + 1) * 10) + to_subtract = Path() + for previous in disjoint_paths: + to_subtract.addPath(previous) + to_subtract.addPath(compound_paths[index + 1]) + try: + result = op(base, to_subtract, PathOp.DIFFERENCE) + except PathOpsError: + break + disjoint_paths.append(result) + + # Remove the padding from each clipped layer. + for index, path in enumerate(disjoint_paths): + try: + disjoint_paths[index] = op( + path, + create_background_rect(img, 0), + PathOp.INTERSECTION, + ) + except PathOpsError: + return compound_paths + processed = len(disjoint_paths) + return disjoint_paths + compound_paths[processed:] diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py index d1ab1ef..6dc3dd2 100644 --- a/vectorizing/tests/test.py +++ b/vectorizing/tests/test.py @@ -94,68 +94,6 @@ def test_write_img_difference_handles_rgba_baselines(tmp_path, monkeypatch): assert output.exists() -def test_color_solver_renders_shared_edges_opaque(): - image = Image.new("RGB", (10, 10), (40, 81, 180)) - for x in range(2, 8): - for y in range(2, 8): - image.putpixel((x, y), (26, 54, 127)) - - paths, colors, width, height = ColorSolver(image, 2, Timer()).solve() - markup = generate_SVG_markup(paths, colors, width, height) - rendered = Image.open( - BytesIO(svg2png(bytestring=markup, output_width=101, output_height=101)), - ).convert("RGBA") - - assert "stroke=" not in markup - assert rendered.getpixel((20, 50))[3] == 255 - - -def test_color_solver_renders_transparent_shared_edges_opaque(): - image = Image.new("RGBA", (10, 10), (0, 0, 0, 0)) - for x in range(1, 9): - for y in range(1, 9): - image.putpixel((x, y), (40, 81, 180, 255)) - for x in range(2, 8): - for y in range(2, 8): - image.putpixel((x, y), (26, 54, 127, 255)) - - paths, colors, width, height = ColorSolver(image, 2, Timer()).solve() - markup = generate_SVG_markup(paths, colors, width, height) - rendered = Image.open( - BytesIO(svg2png(bytestring=markup, output_width=101, output_height=101)), - ).convert("RGBA") - - assert "stroke=" not in markup - assert rendered.getpixel((0, 0))[3] == 0 - assert rendered.getpixel((20, 50))[3] == 255 - - -@pytest.mark.parametrize( - "image_name, color_count", - [("bubbles.png", 5), ("shapes_2.png", 7)], -) -def test_color_solver_renders_real_multicolor_edges_opaque(image_name, color_count): - image = Image.open(Path(__file__).parent / "images" / image_name) - paths, colors, width, height = ColorSolver(image, color_count, Timer()).solve() - markup = generate_SVG_markup(paths, colors, width, height) - rendered = Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA") - - assert "stroke=" not in markup - assert rendered.getchannel("A").getextrema() == (255, 255) - - -def test_color_solver_avoids_transparent_inner_seams_in_aftermath(): - image = Image.open(Path(__file__).parent / "images" / "aftermath.png") - paths, colors, width, height = ColorSolver(image, 16, Timer()).solve() - markup = generate_SVG_markup(paths, colors, width, height) - rendered = Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA") - alpha = list(rendered.getchannel("A").getdata()) - - assert min(alpha) == 0 - assert max(alpha) == 255 - assert sum(0 < value < 255 for value in alpha) < 10_000 - - def test_color_solver_preserves_empty_transparent_image(): image = Image.open(Path(__file__).parent / "images" / "empty.png") paths, colors, width, height = ColorSolver(image, 6, Timer()).solve() diff --git a/vectorizing/tests/test_color_layers.py b/vectorizing/tests/test_color_layers.py new file mode 100644 index 0000000..0663335 --- /dev/null +++ b/vectorizing/tests/test_color_layers.py @@ -0,0 +1,81 @@ +"""Tests for holes left by deleted or transparent color layers.""" + +from io import BytesIO +from unittest.mock import Mock + +import numpy as np +import pytest +from cairosvg import svg2png +from pathops import Path +from PIL import Image + +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup + + +def nested_layers( + monkeypatch: pytest.MonkeyPatch, + transparent: bool, +) -> tuple[list[Path], list[np.ndarray]]: + """Trace three nested color regions with an optional transparent border.""" + labels = np.zeros((40, 40), dtype=np.uint8) + colors = [[220, 40, 40, 255], [40, 180, 40, 255], [40, 40, 220, 255]] + offset = int(transparent) + if transparent: + colors.insert(0, [0, 0, 0, 0]) + labels[4:36, 4:36] = 1 + labels[10:30, 10:30] = 1 + offset + labels[16:24, 16:24] = 2 + offset + palette = np.asarray(colors, dtype=np.uint8) + quantize = Mock(return_value=(labels, palette, transparent)) + monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.quantize", quantize) + paths, retained, _, _ = ColorSolver( + Image.fromarray(palette[labels]), + 3, + Timer(), + ).solve() + quantize.assert_called_once() + return paths, retained + + +def render_layers(paths: list[Path], colors: list[np.ndarray]) -> np.ndarray: + """Render SVG paths as RGBA pixels.""" + markup = generate_SVG_markup(paths, colors, 40, 40) + np.testing.assert_equal("stroke=" in markup, False) + return np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) + + +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("layer", [0, 1, 2]) +@pytest.mark.parametrize("operation", ["remove", "transparent", "half-opacity"]) +def test_editing_a_layer_leaves_a_hole( + monkeypatch: pytest.MonkeyPatch, + transparent: bool, + layer: int, + operation: str, +) -> None: + """Verify layer edits expose transparency without changing other regions.""" + paths, colors = nested_layers(monkeypatch, transparent) + # Sample region interiors, away from anti-aliased boundaries. + samples = [(20, 7), (20, 12), (20, 20)] + original = render_layers(paths, colors) + for point in samples: + np.testing.assert_equal(original[point][3], 255) + + if operation == "remove": + del paths[layer] + del colors[layer] + else: + colors[layer] = colors[layer].copy() + # SVG rgba() uses alpha in [0, 1], unlike the quantizer's uint8 palette. + colors[layer] = colors[layer].astype(float) + colors[layer][3] = 0.5 if operation == "half-opacity" else 0 + edited = render_layers(paths, colors) + expected_alpha = 128 if operation == "half-opacity" else 0 + np.testing.assert_equal(edited[samples[layer]][3], expected_alpha) + for index, point in enumerate(samples): + if index != layer: + np.testing.assert_array_equal(edited[point], original[point]) + if transparent: + np.testing.assert_array_equal(edited[0, 0], [0, 0, 0, 0]) From 0683f7f7b03eba3820265a7827eebd3972d21705 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 11:20:01 +0200 Subject: [PATCH 05/16] fix(ci): avoid duplicate checks on release PRs (#78) --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index b4d5e4f..5af53d3 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -2,7 +2,7 @@ name: ci on: push: branches: - - main + - production pull_request: concurrency: From 3ad2d2915a3299f9bd6c93bd02ab4e9653281ec8 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 11:21:07 +0200 Subject: [PATCH 06/16] fix(color): preserve holes with narrow overlaps at shared edges (#76) * fix(color): restore editable cutouts between color layers * fix(color): trace cutouts with narrow internal edge rims * test(color): guard against cascading rim growth * docs(color): describe clipping behavior without change history --- README.md | 5 + vectorizing/solvers/color/ColorSolver.py | 11 +- vectorizing/solvers/color/bitmaps.py | 20 +++ vectorizing/solvers/color/clip.py | 67 ---------- vectorizing/tests/test_color_bitmap_rims.py | 72 ++++++++++ vectorizing/tests/test_color_layer_artwork.py | 93 +++++++++++++ vectorizing/tests/test_color_layers.py | 126 +++++++++++++++--- 7 files changed, 305 insertions(+), 89 deletions(-) delete mode 100644 vectorizing/solvers/color/clip.py create mode 100644 vectorizing/tests/test_color_bitmap_rims.py create mode 100644 vectorizing/tests/test_color_layer_artwork.py diff --git a/README.md b/README.md index 046f32e..1946d65 100644 --- a/README.md +++ b/README.md @@ -90,6 +90,11 @@ A typical response would be Or, if `raw = true` was supplied, just plain SVG markup +Color layers have cutouts with a small overlap along shared edges to hide seams. +The overlap is two pixels in the resized image before tracing, not screen pixels. +Hiding a color can expose this rim; very thin features may remain covered, and +zooming in makes the rim larger. No SVG strokes are added. + ## Testing Tests work on rasterized versions of vectorized markup. i.e diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index 5d3fbe5..5d07010 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -1,8 +1,8 @@ import numpy as np import potrace -from vectorizing.solvers.color.bitmaps import create_bitmaps -from vectorizing.solvers.color.clip import remove_layering +from vectorizing.geometry.potrace import potrace_path_to_compound_path +from vectorizing.solvers.color.bitmaps import add_bitmap_rims, create_bitmaps from vectorizing.solvers.color.quantize import quantize from vectorizing.util.limit_size import limit_size @@ -28,15 +28,16 @@ def solve(self): self.timer.start_timer("Bitmap Creation") bitmaps, colors = create_bitmaps(labels, colors, has_background) + add_bitmap_rims(bitmaps) self.timer.end_timer() self.timer.start_timer("Bitmap Tracing") traced_bitmaps = [potrace.Bitmap(bitmap).trace() for bitmap in bitmaps] self.timer.end_timer() - self.timer.start_timer("Polygon Clipping") - compound_paths = remove_layering(traced_bitmaps, self.img, has_background) - self.timer.end_timer() + compound_paths = [ + potrace_path_to_compound_path(traced) for traced in traced_bitmaps + ] return [compound_paths, colors, self.img.size[0], self.img.size[1]] diff --git a/vectorizing/solvers/color/bitmaps.py b/vectorizing/solvers/color/bitmaps.py index 1323d1d..a099366 100644 --- a/vectorizing/solvers/color/bitmaps.py +++ b/vectorizing/solvers/color/bitmaps.py @@ -1,5 +1,6 @@ """Build overlapping color masks for Potrace tracing.""" +import cv2 import numpy as np @@ -26,3 +27,22 @@ def create_bitmaps( bitmaps[index] += bitmaps[index + 1] return bitmaps, retained_colors + + +def add_bitmap_rims(bitmaps: list[np.ndarray]) -> None: + """Replace cumulative masks in place with cutouts plus two-pixel inner rims.""" + # One pixel still leaves gaps after curve fitting on the artwork fixtures. + # This is in processed-image pixels, not screen pixels: zoom enlarges the + # lip, and features at most four pixels wide may be covered by neighboring rims. + kernel = np.ones((5, 5), dtype=np.uint8) + # Work forwards while the next mask is still cumulative. Dilation adds only + # neighboring pixels; clipping to this mask excludes earlier colors and + # transparent space. The last mask already contains just its own color. + for bitmap, above in zip(bitmaps, bitmaps[1:]): + visible = (bitmap > above).astype(np.uint8) + bitmap &= cv2.dilate( + visible, + kernel, + borderType=cv2.BORDER_CONSTANT, + borderValue=0, + ) diff --git a/vectorizing/solvers/color/clip.py b/vectorizing/solvers/color/clip.py deleted file mode 100644 index 0520d7b..0000000 --- a/vectorizing/solvers/color/clip.py +++ /dev/null @@ -1,67 +0,0 @@ -"""Cut overlapping color paths into separate regions.""" - -import potrace -from pathops import Path, PathOp, PathOpsError, op -from PIL import Image - -from vectorizing.geometry.potrace import potrace_path_to_compound_path - - -def create_background_rect(img: Image.Image, padding: int) -> Path: - """Return the image rectangle expanded by padding on every side.""" - rect = Path() - rect.moveTo(-padding, -padding) - rect.lineTo(img.width + padding, -padding) - rect.lineTo(img.width + padding, img.height + padding) - rect.lineTo(-padding, img.height + padding) - rect.close() - return rect - - -def remove_layering( - traced_bitmaps: list[potrace.Path], - img: Image.Image, - has_background: bool, -) -> list[Path]: - """Subtract later colors from lower layers, retaining overlap if clipping fails.""" - compound_paths = [ - potrace_path_to_compound_path(traced) for traced in traced_bitmaps - ] - if has_background: - for index in range(len(compound_paths) - 1): - try: - compound_paths[index] = op( - compound_paths[index], - compound_paths[index + 1], - PathOp.DIFFERENCE, - ) - except PathOpsError: - break - return compound_paths - - disjoint_paths = [] - for index in range(len(compound_paths) - 1): - # Different padding keeps the rectangles' outer edges from coinciding. - base = create_background_rect(img, (index + 1) * 10) - to_subtract = Path() - for previous in disjoint_paths: - to_subtract.addPath(previous) - to_subtract.addPath(compound_paths[index + 1]) - try: - result = op(base, to_subtract, PathOp.DIFFERENCE) - except PathOpsError: - break - disjoint_paths.append(result) - - # Remove the padding from each clipped layer. - for index, path in enumerate(disjoint_paths): - try: - disjoint_paths[index] = op( - path, - create_background_rect(img, 0), - PathOp.INTERSECTION, - ) - except PathOpsError: - return compound_paths - processed = len(disjoint_paths) - return disjoint_paths + compound_paths[processed:] diff --git a/vectorizing/tests/test_color_bitmap_rims.py b/vectorizing/tests/test_color_bitmap_rims.py new file mode 100644 index 0000000..788cf00 --- /dev/null +++ b/vectorizing/tests/test_color_bitmap_rims.py @@ -0,0 +1,72 @@ +"""Bound overlap at the bitmap stage independently of Potrace's curve fitting.""" + +import numpy as np +import pytest + +from vectorizing.solvers.color.bitmaps import add_bitmap_rims, create_bitmaps + + +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("shape", [(1, 1), (1, 9), (9, 1), (8, 13)]) +@pytest.mark.parametrize("seed", range(5)) +def test_bitmap_rims_match_a_bounded_neighbor_reference( + transparent: bool, + shape: tuple[int, int], + seed: int, +) -> None: + """Add only later-color pixels within two grid cells of this color's own pixels.""" + labels = np.random.default_rng(seed).integers(0, 5, size=shape) + colors = np.arange(15).reshape(5, 3) + masks, retained = create_bitmaps(labels, colors, transparent) + ids = [id(mask) for mask in masks] + expected = [] + # A direct pixel loop is deliberately independent of OpenCV dilation and + # cumulative-mask mutation. Missing palette colors must not affect ordering. + for color in retained: + index = int(color[0] // 3) + own = labels == index + neighbors = np.zeros(shape, dtype=bool) + for y, x in np.argwhere(own): + top, bottom = max(0, y - 2), y + 3 + left, right = max(0, x - 2), x + 3 + neighbors[top:bottom, left:right] = True + expected.append((neighbors & (labels >= index)).astype(np.uint32)) + add_bitmap_rims(masks) + np.testing.assert_equal([id(mask) for mask in masks], ids) + for actual, reference in zip(masks, expected): + np.testing.assert_array_equal(actual, reference) + np.testing.assert_equal(actual.dtype, np.dtype(np.uint32)) + # Every original foreground pixel remains covered; no transparent background + # pixel becomes painted, even where it touches several colors. + combined = np.any(masks, axis=0) if masks else np.zeros(shape, dtype=bool) + np.testing.assert_array_equal(combined, labels != 0 if transparent else True) + + +def test_bitmap_rims_do_not_cascade_through_later_colors() -> None: + """Keep distant colors out of lower masks when converting cumulative storage.""" + # Dense random labels can hide a reversed loop: every color is nearby. Wide + # strips ensure that a modified upper mask cannot masquerade as this color. + labels = np.tile(np.repeat(np.arange(4), 10), (12, 1)) + masks, _ = create_bitmaps(labels, np.zeros((4, 3)), False) + add_bitmap_rims(masks) + for index, mask in enumerate(masks): + expected = np.zeros_like(mask) + left, right = index * 10, min((index + 1) * 10 + 2, 40) + expected[:, left:right] = 1 + np.testing.assert_array_equal(mask, expected) + + +def test_bitmap_rims_handle_empty_input() -> None: + """Leave empty artwork empty.""" + masks = [] + add_bitmap_rims(masks) + np.testing.assert_equal(masks, []) + + +def test_bitmap_rims_document_the_thin_feature_tradeoff() -> None: + """Document that a narrow strip can be covered entirely by a neighboring rim.""" + labels = np.zeros((12, 12), dtype=int) + labels[:, 5:7] = 1 + masks, _ = create_bitmaps(labels, np.zeros((2, 3)), False) + add_bitmap_rims(masks) + np.testing.assert_array_equal(masks[0][:, 5:7], 1) diff --git a/vectorizing/tests/test_color_layer_artwork.py b/vectorizing/tests/test_color_layer_artwork.py new file mode 100644 index 0000000..217e070 --- /dev/null +++ b/vectorizing/tests/test_color_layer_artwork.py @@ -0,0 +1,93 @@ +"""Check rim rendering and edited holes on the real artwork fixtures.""" + +from io import BytesIO +from pathlib import Path +from unittest.mock import Mock + +import numpy as np +import potrace +import pytest +from cairosvg import svg2png +from PIL import Image +from scipy.ndimage import distance_transform_edt + +from vectorizing.geometry.potrace import potrace_path_to_compound_path +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.bitmaps import add_bitmap_rims +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup + + +@pytest.mark.parametrize("filename, count", [("bubbles.png", 5), ("shapes_2.png", 7)]) +def test_opaque_artwork_has_no_alpha_seams(filename: str, count: int) -> None: + """Keep opaque artwork opaque through every shared boundary.""" + with Image.open(Path(__file__).parent / "images" / filename) as image: + result = ColorSolver(image, count, Timer()).solve() + markup = generate_SVG_markup(*result) + pixels = np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) + np.testing.assert_array_equal(pixels[:, :, 3], 255) + np.testing.assert_equal("stroke=" in markup, False) + + +def test_aftermath_retains_holes_when_layers_are_edited( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep the exterior transparent and reveal holes, not underpainting, on edits.""" + foreground = [] + + def capture_foreground(masks: list[np.ndarray]) -> None: + foreground.append(masks[0].copy()) + add_bitmap_rims(masks) + + rim_builder = Mock(side_effect=capture_foreground) + monkeypatch.setattr( + "vectorizing.solvers.color.ColorSolver.add_bitmap_rims", + rim_builder, + ) + with Image.open(Path(__file__).parent / "images" / "aftermath.png") as image: + paths, colors, width, height = ColorSolver(image, 16, Timer()).solve() + rim_builder.assert_called_once() + silhouette = potrace_path_to_compound_path(potrace.Bitmap(foreground[0]).trace()) + silhouette_svg = generate_SVG_markup([silhouette], [[0, 0, 0]], width, height) + silhouette_alpha = np.asarray( + Image.open(BytesIO(svg2png(bytestring=silhouette_svg))).convert("RGBA"), + )[:, :, 3] + markup = generate_SVG_markup(paths, colors, width, height) + full = np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) + np.testing.assert_equal(full[:, :, 3].min(), 0) + np.testing.assert_equal(full[:, :, 3].max(), 255) + # Allow smooth exterior edges, but catch broad interior seam regressions. + alpha = full[:, :, 3] + # Unlike a total partial-alpha budget, this checks where gaps occur. Allow + # a 3-pixel band by the exterior: separately fitted curves can differ there. + interior = distance_transform_edt(silhouette_alpha == 255) > 3 + np.testing.assert_equal(interior.any(), True) + np.testing.assert_array_equal(alpha[interior], 255) + exterior = distance_transform_edt(silhouette_alpha == 0) > 3 + np.testing.assert_array_equal(alpha[exterior], 0) + np.testing.assert_equal( + np.count_nonzero((alpha > 0) & (alpha < 255)) < 10_000, + True, + ) + for index in [0, len(paths) // 2, len(paths) - 1]: + solo = generate_SVG_markup([paths[index]], [colors[index]], width, height) + solo_alpha = np.asarray( + Image.open(BytesIO(svg2png(bytestring=solo))).convert("RGBA"), + )[:, :, 3] + # Select a point far inside the color, excluding its intentionally narrow rim. + distances = distance_transform_edt(solo_alpha == 255) + np.testing.assert_equal(distances.max() > 2, True) + point = np.unravel_index(distances.argmax(), distances.shape) + for opacity in [None, 0, 0.5]: + edited_paths, edited_colors = list(paths), list(colors) + if opacity is None: + del edited_paths[index] + del edited_colors[index] + else: + edited_colors[index] = np.array([*colors[index][:3], opacity]) + edited = generate_SVG_markup(edited_paths, edited_colors, width, height) + pixels = np.asarray( + Image.open(BytesIO(svg2png(bytestring=edited))).convert("RGBA"), + ) + np.testing.assert_equal(pixels[point][3], 128 if opacity == 0.5 else 0) + np.testing.assert_equal(pixels[0, 0, 3], 0) diff --git a/vectorizing/tests/test_color_layers.py b/vectorizing/tests/test_color_layers.py index 0663335..c14bb05 100644 --- a/vectorizing/tests/test_color_layers.py +++ b/vectorizing/tests/test_color_layers.py @@ -14,6 +14,24 @@ from vectorizing.svg.markup import generate_SVG_markup +def trace_layers( + monkeypatch: pytest.MonkeyPatch, + labels: np.ndarray, + palette: np.ndarray, + transparent: bool, +) -> tuple[list[Path], list[np.ndarray]]: + """Exercise bitmap creation and tracing with known labels, bypassing clustering.""" + quantize = Mock(return_value=(labels, palette, transparent)) + monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.quantize", quantize) + paths, retained, _, _ = ColorSolver( + Image.fromarray(palette[labels]), + 3, + Timer(), + ).solve() + quantize.assert_called_once() + return paths, retained + + def nested_layers( monkeypatch: pytest.MonkeyPatch, transparent: bool, @@ -27,23 +45,25 @@ def nested_layers( labels[4:36, 4:36] = 1 labels[10:30, 10:30] = 1 + offset labels[16:24, 16:24] = 2 + offset - palette = np.asarray(colors, dtype=np.uint8) - quantize = Mock(return_value=(labels, palette, transparent)) - monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.quantize", quantize) - paths, retained, _, _ = ColorSolver( - Image.fromarray(palette[labels]), - 3, - Timer(), - ).solve() - quantize.assert_called_once() - return paths, retained + return trace_layers( + monkeypatch, + labels, + np.asarray(colors, dtype=np.uint8), + transparent, + ) -def render_layers(paths: list[Path], colors: list[np.ndarray]) -> np.ndarray: +def render_layers( + paths: list[Path], + colors: list[np.ndarray], + size: int = 40, +) -> np.ndarray: """Render SVG paths as RGBA pixels.""" markup = generate_SVG_markup(paths, colors, 40, 40) np.testing.assert_equal("stroke=" in markup, False) - return np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) + np.testing.assert_equal("crispEdges" in markup, False) + png = svg2png(bytestring=markup, output_width=size, output_height=size) + return np.asarray(Image.open(BytesIO(png)).convert("RGBA")) @pytest.mark.parametrize("transparent", [False, True]) @@ -62,20 +82,92 @@ def test_editing_a_layer_leaves_a_hole( original = render_layers(paths, colors) for point in samples: np.testing.assert_equal(original[point][3], 255) - if operation == "remove": del paths[layer] del colors[layer] else: - colors[layer] = colors[layer].copy() - # SVG rgba() uses alpha in [0, 1], unlike the quantizer's uint8 palette. colors[layer] = colors[layer].astype(float) + # SVG rgba() uses alpha in [0, 1], unlike the quantizer's uint8 palette. colors[layer][3] = 0.5 if operation == "half-opacity" else 0 edited = render_layers(paths, colors) - expected_alpha = 128 if operation == "half-opacity" else 0 - np.testing.assert_equal(edited[samples[layer]][3], expected_alpha) + np.testing.assert_equal( + edited[samples[layer]][3], + 128 if operation == "half-opacity" else 0, + ) for index, point in enumerate(samples): if index != layer: np.testing.assert_array_equal(edited[point], original[point]) if transparent: np.testing.assert_array_equal(edited[0, 0], [0, 0, 0, 0]) + + +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("size", [40, 101, 160]) +def test_rims_cover_shared_edges( + monkeypatch: pytest.MonkeyPatch, + transparent: bool, + size: int, +) -> None: + """Hide interior alpha seams at native, fractional and enlarged render scales.""" + paths, colors = nested_layers(monkeypatch, transparent) + pixels = render_layers(paths, colors, size) + inset = size // 5 + np.testing.assert_array_equal(pixels[inset:-inset, inset:-inset, 3], 255) + + +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("layer, edge", [(0, 10), (1, 16)]) +def test_rims_are_narrow_and_only_under_later_colors( + monkeypatch: pytest.MonkeyPatch, + transparent: bool, + layer: int, + edge: int, +) -> None: + """Allow a small lip, not full underpainting or a shifted visible edge.""" + paths, _ = nested_layers(monkeypatch, transparent) + np.testing.assert_equal(paths[layer].contains((edge + 0.25, 20)), True) + np.testing.assert_equal(paths[layer].contains((edge + 2.25, 20)), False) + if layer == 1: + np.testing.assert_equal(paths[layer].contains((9.75, 20)), False) + for path in paths: + np.testing.assert_equal(path.contains((-0.25, 20)), False) + if transparent: + np.testing.assert_equal(path.contains((3.75, 20)), False) + + +@pytest.mark.parametrize("size", [40, 101, 160]) +def test_rims_cover_three_color_junctions( + monkeypatch: pytest.MonkeyPatch, + size: int, +) -> None: + """Check a T junction, where more than two independently traced colors meet.""" + labels = np.zeros((40, 40), dtype=np.uint8) + labels[:, 20:] = 1 + labels[20:, 20:] = 2 + palette = np.array([[220, 0, 0], [0, 180, 0], [0, 0, 220]], dtype=np.uint8) + paths, colors = trace_layers(monkeypatch, labels, palette, False) + np.testing.assert_array_equal( + render_layers(paths, colors, size)[2:-2, 2:-2, 3], + 255, + ) + + +def test_rims_leave_transparent_holes_and_islands_alone( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep background holes and gaps empty; do not leave ghosts of distant colors.""" + labels = np.zeros((40, 40), dtype=np.uint8) + labels[2:18, 2:18] = 1 + labels[6:14, 6:14] = 0 + labels[24:36, 24:36] = 2 + palette = np.array( + [[0, 0, 0, 0], [220, 0, 0, 255], [0, 0, 220, 255]], + dtype=np.uint8, + ) + paths, colors = trace_layers(monkeypatch, labels, palette, True) + pixels = render_layers(paths, colors) + np.testing.assert_array_equal(pixels[8:12, 8:12, 3], 0) + np.testing.assert_array_equal(pixels[19:22, 19:22, 3], 0) + # Removing the distant blue island must not leave even a red outline behind. + removed = render_layers(paths[:1], colors[:1]) + np.testing.assert_array_equal(removed[22:38, 22:38, 3], 0) From 4762b9a8c081888b1d69fc85706bf125539e67c0 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 12:49:56 +0200 Subject: [PATCH 07/16] chore(lint): restore passing repository checks (#79) chore(lint): clean up checks without changing behavior Pin compatible lint tools and complete formatting, annotations and documentation. Preserve image-loading failure behavior with narrow exemptions and add 50 compatibility cases. Verified 508 tests, passing hooks on Python 3.11/3.12, and 15 identical SVG and raster output comparisons. --- .pre-commit-config.yaml | 25 ++-- pyproject.toml | 5 + scripts/init_moto.py | 3 +- vectorizing/__init__.py | 149 ++++++++++++--------- vectorizing/geometry/bounds.py | 16 +-- vectorizing/geometry/potrace.py | 18 +-- vectorizing/server/env.py | 33 +++-- vectorizing/server/logs.py | 49 +++---- vectorizing/server/s3.py | 19 ++- vectorizing/server/timer.py | 26 ++-- vectorizing/solvers/binary/BinarySolver.py | 11 +- vectorizing/solvers/binary/bitmap.py | 26 ++-- vectorizing/solvers/color/ColorSolver.py | 12 +- vectorizing/solvers/color/quantize.py | 117 +++++++++------- vectorizing/svg/markup.py | 64 +++------ vectorizing/tests/__init__.py | 1 + vectorizing/tests/config.py | 65 +++------ vectorizing/tests/conftest.py | 6 +- vectorizing/tests/test.py | 23 ++-- vectorizing/tests/test_api_contracts.py | 116 ++++++++++++++++ vectorizing/tests/test_image_reading.py | 116 ++++++++++++++++ vectorizing/tests/test_svg_markup.py | 76 +++++++++++ vectorizing/tests/testutil.py | 115 ++++------------ vectorizing/util/limit_size.py | 21 ++- vectorizing/util/read.py | 79 +++++++---- 25 files changed, 740 insertions(+), 451 deletions(-) create mode 100644 vectorizing/tests/test_api_contracts.py create mode 100644 vectorizing/tests/test_image_reading.py create mode 100644 vectorizing/tests/test_svg_markup.py diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 2175768..d6a4660 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -23,23 +23,24 @@ repos: # flake8 python linter with all the fixins - repo: https://github.com/PyCQA/flake8 - rev: 6.0.0 + rev: 7.3.0 hooks: # additional configuration of flake8 and extensions in pyproject.toml - id: flake8 additional_dependencies: [ - flake8-annotations, - flake8-bandit, - flake8-bugbear, - flake8-black, - flake8-docstrings, - flake8-import-order, - darglint, - mypy, - pycodestyle, - pydocstyle, - Flake8-pyproject + flake8-annotations==3.2.0, + flake8-bandit==4.1.1, + bandit==1.9.4, + flake8-bugbear==24.12.12, + flake8-black==0.4.0, + black==23.1.0, + flake8-docstrings==1.7.0, + flake8-import-order==0.19.2, + darglint==1.8.1, + pycodestyle==2.14.0, + pydocstyle==6.3.0, + Flake8-pyproject==1.2.4 ] # removed unused imports and variables diff --git a/pyproject.toml b/pyproject.toml index 158e06f..1bfb6f4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,7 +16,12 @@ extend-ignore = [ 'I100', 'I101', 'I202', + # Black controls whitespace in complex slices. + 'E203', + # The containing class already determines the type of self. + 'ANN101', ] +per-file-ignores = ['vectorizing/tests/*:S101'] import-order-style = "google" docstring-convention = "numpy" strictness = "short" diff --git a/scripts/init_moto.py b/scripts/init_moto.py index 4bad201..b6426b4 100644 --- a/scripts/init_moto.py +++ b/scripts/init_moto.py @@ -1,8 +1,9 @@ +"""Create separate local application and test buckets if they do not exist.""" + import os import boto3 - s3 = boto3.client("s3", endpoint_url=os.environ["AWS_ENDPOINT_URL"]) existing = {bucket["Name"] for bucket in s3.list_buckets()["Buckets"]} diff --git a/vectorizing/__init__.py b/vectorizing/__init__.py index 879184e..1abf422 100644 --- a/vectorizing/__init__.py +++ b/vectorizing/__init__.py @@ -1,17 +1,24 @@ +"""Expose image vectorization and health checks through Flask.""" + import os -import sentry_sdk from types import SimpleNamespace -from flask import Flask, request, jsonify +from typing import Literal, NoReturn -from vectorizing.server.timer import Timer +import numpy as np +import sentry_sdk +from flask import Flask, Response, jsonify, request +from pathops import Path +from PIL import Image + +from vectorizing.geometry.bounds import compound_paths_bounds +from vectorizing.server.env import get_optional, get_required from vectorizing.server.logs import setup_logs from vectorizing.server.s3 import upload_markup +from vectorizing.server.timer import Timer +from vectorizing.solvers.binary.BinarySolver import BinarySolver +from vectorizing.solvers.color.ColorSolver import ColorSolver from vectorizing.svg.markup import generate_SVG_markup from vectorizing.util.read import try_read_image_from_url -from vectorizing.server.env import get_required, get_optional -from vectorizing.solvers.color.ColorSolver import ColorSolver -from vectorizing.solvers.binary.BinarySolver import BinarySolver -from vectorizing.geometry.bounds import compound_paths_bounds # 0 -> BinarySolver # 1 -> ColorSolver @@ -24,30 +31,37 @@ S3_BUCKET, ) = get_required() -( - SENTRY_DSN, - S3_TEST_BUCKET -) = get_optional() +(SENTRY_DSN, S3_TEST_BUCKET) = get_optional() setup_logs() -def process_binary(img): + +def process_binary(img: Image.Image) -> tuple[list[Path], list[list[int]], int, int]: + """Trace an image into black paths and return its processed dimensions.""" solver = BinarySolver(img) return solver.solve() -def process_color(img, color_count, timer): + +def process_color( + img: Image.Image, + color_count: int | None, + timer: Timer, +) -> list[list[Path] | list[np.ndarray] | int]: + """Trace color layers with bounded overlaps and return processed dimensions.""" solver = ColorSolver(img, color_count, timer) return solver.solve() -def validate_args(args): - if not 'url' in args: + +def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: + """Validate the URL key, solver choice and optional four-integer crop box.""" + if "url" not in args: return False - solver = args.get('solver', DEFAULT_SOLVER) - if not solver in SOLVERS: + solver = args.get("solver", DEFAULT_SOLVER) + if solver not in SOLVERS: return False - box = args.get('crop_box') + box = args.get("crop_box") if box: if len(box) != 4: return False @@ -61,21 +75,22 @@ def validate_args(args): solver=solver, url=args.get("url"), raw=args.get("raw"), - color_count=args.get("color_count") + color_count=args.get("color_count"), ) -def invalid_args(): - return jsonify({ - "success": False, - "error": "INVALID_PARAMETERS" - }), 400 -def create_app(test_config=None): +def invalid_args() -> tuple[Response, int]: + """Return the API's invalid-parameters response.""" + return jsonify({"success": False, "error": "INVALID_PARAMETERS"}), 400 + + +def create_app(test_config: dict[str, object] | None = None) -> Flask: + """Create the HTTP app; the optional test_config argument is unused.""" app = Flask(__name__, instance_relative_config=True) - app.debug = PYTHON_ENV == 'development' + app.debug = PYTHON_ENV == "development" - @app.route('/', methods = ['POST']) - def index(): + @app.route("/", methods=["POST"]) + def index() -> str | Response | tuple[Response, int]: args = request.json args = validate_args(args) @@ -91,7 +106,7 @@ def index(): try: timer = Timer() - timer.start_timer('Image Reading') + timer.start_timer("Image Reading") img = try_read_image_from_url(url) timer.end_timer() @@ -99,66 +114,72 @@ def index(): img = img.crop(tuple(crop_box)) if solver == 0: - timer.start_timer('Binary Solver - Total') + timer.start_timer("Binary Solver - Total") solved = process_binary(img) timer.end_timer() else: - timer.start_timer('Color Solver - Total') + timer.start_timer("Color Solver - Total") solved = process_color(img, color_count, timer) timer.end_timer() compound_paths, colors, width, height = solved - timer.start_timer('Markup Creation') + timer.start_timer("Markup Creation") markup = generate_SVG_markup(compound_paths, colors, width, height) timer.end_timer() if raw: return markup - timer.start_timer('Markup Upload') + timer.start_timer("Markup Upload") cuid_str = upload_markup(markup, S3_BUCKET) timer.end_timer() - timer.start_timer('Bounds Creation') + timer.start_timer("Bounds Creation") bounds = compound_paths_bounds(compound_paths) timer.end_timer() app.logger.info(timer.timelog()) - return jsonify({ - 'success': True, - 'objectId': cuid_str, - 'info': { - 'bounds': bounds, - 'image_width': width, - 'image_height': height - } - }) - - except (Exception) as e: + return jsonify( + { + "success": True, + "objectId": cuid_str, + "info": { + "bounds": bounds, + "image_width": width, + "image_height": height, + }, + }, + ) + + except Exception as e: app.logger.error(e) - return jsonify({ - "success": False, - "error": "INTERNAL_SERVER_ERROR" - }), 500 - - @app.route('/health', methods = ['GET']) - def healthcheck(): - return jsonify({ - "success": True, - }), 200 - - @app.route('/test-error', methods = ['GET']) - def test_error(): - raise Exception('Test Error') - - app.logger.info(f'Vectorizing server running on port: {PORT}, environment: {PYTHON_ENV}') + return jsonify({"success": False, "error": "INTERNAL_SERVER_ERROR"}), 500 + + @app.route("/health", methods=["GET"]) + def healthcheck() -> tuple[Response, int]: + return ( + jsonify( + { + "success": True, + }, + ), + 200, + ) + + @app.route("/test-error", methods=["GET"]) + def test_error() -> NoReturn: + raise Exception("Test Error") + + app.logger.info( + f"Vectorizing server running on port: {PORT}, environment: {PYTHON_ENV}", + ) if SENTRY_DSN: sentry_sdk.init( - dsn = SENTRY_DSN, - traces_sample_rate = 0.1, - environment = PYTHON_ENV, + dsn=SENTRY_DSN, + traces_sample_rate=0.1, + environment=PYTHON_ENV, ) return app diff --git a/vectorizing/geometry/bounds.py b/vectorizing/geometry/bounds.py index 0931cc9..cc563d4 100644 --- a/vectorizing/geometry/bounds.py +++ b/vectorizing/geometry/bounds.py @@ -1,17 +1,13 @@ -import numpy as np +"""Compute document bounds from traced vector paths.""" +from collections.abc import Iterable -# Calculates bounds of a list of compound paths -def compound_paths_bounds(compound_paths): - """ - Calculates the combined bounds of a list of compound paths. +import numpy as np +from pathops import Path - Parameters: - compound_paths: The list of compound paths (SKPath). - Returns: - An object containing combined bounds info. - """ +def compound_paths_bounds(compound_paths: Iterable[Path]) -> dict[str, float]: + """Return combined bounds, retaining infinite extents for an empty iterable.""" min_x = np.inf min_y = np.inf max_x = -np.inf diff --git a/vectorizing/geometry/potrace.py b/vectorizing/geometry/potrace.py index 521cdb7..64b8232 100644 --- a/vectorizing/geometry/potrace.py +++ b/vectorizing/geometry/potrace.py @@ -1,19 +1,11 @@ -import numpy as np -from pathops import Path, FillType +"""Convert Potrace curves into paths suitable for SVG serialization.""" +import potrace +from pathops import FillType, Path -def potrace_path_to_compound_path(potrace_path): - """ - Converts a potrace path into an SKPath. - This conversion is needed to later perform boolean operations - on compound paths. - Parameters: - potrace_path: The potrace path - - Returns: - The SKPath - """ +def potrace_path_to_compound_path(potrace_path: potrace.Path) -> Path: + """Convert Potrace curves to an even-odd path of lines and cubic Beziers.""" compound_path = Path(fillType=FillType.EVEN_ODD) for potrace_curve in potrace_path: diff --git a/vectorizing/server/env.py b/vectorizing/server/env.py index b7f37c9..4adb9ae 100644 --- a/vectorizing/server/env.py +++ b/vectorizing/server/env.py @@ -1,33 +1,32 @@ +"""Read and cast the application's ordered environment settings.""" + import os -REQUIRED_ENVIRONMENT_VARIABLES = { - 'PORT': int, - 'S3_BUCKET': str -} +REQUIRED_ENVIRONMENT_VARIABLES = {"PORT": int, "S3_BUCKET": str} + +OPTIONAL_ENVIRONMENT_VARIABLES = {"SENTRY_DSN": str, "S3_TEST_BUCKET": str} -OPTIONAL_ENVIRONMENT_VARIABLES = { - 'SENTRY_DSN': str, - 'S3_TEST_BUCKET': str -} class VariableNotDefinedException(Exception): - pass + """Signal that at least one required environment setting is missing.""" -def get_required(): - missing_required = any([ - not key in os.environ - for key in REQUIRED_ENVIRONMENT_VARIABLES - ]) + +def get_required() -> list[int | str]: + """Return port and bucket, raising if either required setting is missing.""" + missing_required = any( + [key not in os.environ for key in REQUIRED_ENVIRONMENT_VARIABLES], + ) if missing_required: raise VariableNotDefinedException() return [ - cast(os.environ[key]) - for key, cast in REQUIRED_ENVIRONMENT_VARIABLES.items() + cast(os.environ[key]) for key, cast in REQUIRED_ENVIRONMENT_VARIABLES.items() ] -def get_optional(): + +def get_optional() -> list[str | None]: + """Return Sentry DSN and test bucket in order, using None for unset values.""" return [ cast(os.environ[key]) if key in os.environ else None for key, cast in OPTIONAL_ENVIRONMENT_VARIABLES.items() diff --git a/vectorizing/server/logs.py b/vectorizing/server/logs.py index d63b170..93b24b8 100644 --- a/vectorizing/server/logs.py +++ b/vectorizing/server/logs.py @@ -1,33 +1,24 @@ +"""Configure application logging to standard output.""" + from logging.config import dictConfig -def setup_logs(): + +def setup_logs() -> None: + """Configure the root logger with the service's INFO-level stdout format.""" # Set up Flask logging to STDOUT - dictConfig({ - 'version': 1, - 'formatters': - { - 'default': - { - 'format': '[%(levelname)s] %(message)s' - } + dictConfig( + { + "version": 1, + "formatters": {"default": {"format": "[%(levelname)s] %(message)s"}}, + "handlers": { + "stdout": { + "class": "logging.StreamHandler", + "formatter": "default", + "stream": "ext://sys.stdout", + }, + }, + "loggers": { + "": {"handlers": ["stdout"], "level": "INFO", "propagate": True}, }, - 'handlers': - { - 'stdout': - { - 'class': 'logging.StreamHandler', - 'formatter': 'default', - 'stream': 'ext://sys.stdout' - } - }, - 'loggers': - { - '': - { - 'handlers': ['stdout'], - 'level': 'INFO', - 'propagate': True - } - } - } - ) \ No newline at end of file + }, + ) diff --git a/vectorizing/server/s3.py b/vectorizing/server/s3.py index 4316e4f..d5c07e2 100644 --- a/vectorizing/server/s3.py +++ b/vectorizing/server/s3.py @@ -1,13 +1,17 @@ +"""Store SVGs and test images in AWS S3 or an explicitly configured endpoint.""" + import os from functools import lru_cache import boto3 import cuid +from botocore.client import BaseClient from botocore.exceptions import ClientError @lru_cache(maxsize=1) -def get_s3_client(): +def get_s3_client() -> BaseClient: + """Cache the S3 client, honoring AWS_ENDPOINT_URL only when explicitly set.""" endpoint_url = os.getenv("AWS_ENDPOINT_URL") or None return boto3.client( "s3", @@ -16,7 +20,8 @@ def get_s3_client(): ) -def upload_markup(markup, s3_bucket_name): +def upload_markup(markup: str, s3_bucket_name: str) -> str: + """Upload UTF-8 SVG markup under a generated key and return that key.""" cuid_str = cuid.cuid() get_s3_client().put_object( @@ -29,7 +34,8 @@ def upload_markup(markup, s3_bucket_name): return cuid_str -def get_object_url(s3_file_key, s3_bucket_name): +def get_object_url(s3_file_key: str, s3_bucket_name: str) -> str | None: + """Return an existing object's URL, keeping signatures for custom endpoints.""" s3 = get_s3_client() try: s3.head_object( @@ -48,7 +54,12 @@ def get_object_url(s3_file_key, s3_bucket_name): return object_url if os.getenv("AWS_ENDPOINT_URL") else object_url.split("?")[0] -def upload_file(local_file_path, s3_bucket_name, s3_file_key): +def upload_file( + local_file_path: str | os.PathLike[str], + s3_bucket_name: str, + s3_file_key: str, +) -> str | None: + """Upload a local file and return the stored object's URL.""" get_s3_client().upload_file( local_file_path, s3_bucket_name, diff --git a/vectorizing/server/timer.py b/vectorizing/server/timer.py index 4e6cb0c..c91c60d 100644 --- a/vectorizing/server/timer.py +++ b/vectorizing/server/timer.py @@ -1,23 +1,31 @@ +"""Collect named timings, including nested processing stages.""" + import time + class Timer: - def __init__(self): + """Measure nested stages and retain the latest duration for each name.""" + + def __init__(self) -> None: self.entries = {} self.actions_stack = [] self.time_stack = [] - def start_timer(self, action_name): + def start_timer(self, action_name: str) -> None: + """Start a named stage without ending any enclosing stage.""" self.time_stack.append(time.time()) self.actions_stack.append(action_name) - - def end_timer(self): + + def end_timer(self) -> None: + """Record elapsed time for the most recently started stage.""" self.entries[self.actions_stack.pop()] = time.time() - self.time_stack.pop() - def timelog(self): - log = '' + def timelog(self) -> str: + """Format recorded stages in insertion order with a trailing separator.""" + log = "" for action_name in self.entries: time = self.entries[action_name] - log += f'{action_name}: {time} / ' - - return log \ No newline at end of file + log += f"{action_name}: {time} / " + + return log diff --git a/vectorizing/solvers/binary/BinarySolver.py b/vectorizing/solvers/binary/BinarySolver.py index bd8b5a2..5eb1367 100644 --- a/vectorizing/solvers/binary/BinarySolver.py +++ b/vectorizing/solvers/binary/BinarySolver.py @@ -1,5 +1,9 @@ +"""Trace an image into a single black vector layer.""" + import numpy as np import potrace +from pathops import Path +from PIL import Image from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.solvers.binary.bitmap import compute_bitmap @@ -7,13 +11,16 @@ class BinarySolver: - def __init__(self, img): + """Resize, threshold and trace an RGB or RGBA image.""" + + def __init__(self, img: Image.Image) -> None: self.img = limit_size(img) # Init image array self.img_arr = np.asarray(self.img).astype(np.uint8) - def solve(self): + def solve(self) -> tuple[list[Path], list[list[int]], int, int]: + """Return the traced path, black RGBA color and processed image size.""" width, height = self.img.size bitmap = compute_bitmap(self.img_arr) traced_bitmap = potrace.Bitmap(bitmap).trace() diff --git a/vectorizing/solvers/binary/bitmap.py b/vectorizing/solvers/binary/bitmap.py index ffb2334..845d13c 100644 --- a/vectorizing/solvers/binary/bitmap.py +++ b/vectorizing/solvers/binary/bitmap.py @@ -1,9 +1,11 @@ +"""Prepare foreground masks for monochrome tracing.""" + import cv2 import numpy as np -# Inverts an image -def invert(img_arr): +def invert(img_arr: np.ndarray) -> np.ndarray: + """Invert RGB channels while leaving any alpha channel unchanged.""" channel_count = img_arr.shape[-1] if channel_count == 4: @@ -16,10 +18,8 @@ def invert(img_arr): return 255 - img_arr -# Blends a transparent image with a white background by -# interpolating linearly. In the end, an RGBA image -# is turned into RGB -def alpha_blend(img_arr): +def alpha_blend(img_arr: np.ndarray) -> np.ndarray: + """Composite uint8 RGBA pixels over white and return uint8 RGB pixels.""" r, g, b, a = cv2.split(img_arr) n_alpha = a / 255 @@ -30,8 +30,8 @@ def alpha_blend(img_arr): return cv2.merge((r, g, b)).astype(np.uint8) -# Compute threshold -def threshold(img_arr): +def threshold(img_arr: np.ndarray) -> np.ndarray: + """Apply Otsu thresholding, marking dark pixels as foreground.""" channel_count = img_arr.shape[-1] if channel_count == 4: @@ -46,11 +46,11 @@ def threshold(img_arr): return np.where(thresholded >= 128, 0, 1) -# Creates bitmap to be traced by potrace -# This deals with a very common edge case: when an image has a transparent -# background and a white foreground, the alpha blend strips all information, so in -# that case we choose the inverted version -def compute_bitmap(img_arr, foreground_area_threshold=0.01): +def compute_bitmap( + img_arr: np.ndarray, + foreground_area_threshold: float = 0.01, +) -> np.ndarray: + """Select a foreground mask, falling back to a solid mask when it is empty.""" # compute bitmap bitmap = threshold(img_arr) foreground_area = np.sum(bitmap) diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index 5d07010..545c833 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -1,14 +1,21 @@ +"""Trace editable color layers with bounded overlap at shared edges.""" + import numpy as np import potrace +from pathops import Path +from PIL import Image from vectorizing.geometry.potrace import potrace_path_to_compound_path +from vectorizing.server.timer import Timer from vectorizing.solvers.color.bitmaps import add_bitmap_rims, create_bitmaps from vectorizing.solvers.color.quantize import quantize from vectorizing.util.limit_size import limit_size class ColorSolver: - def __init__(self, img, color_count, timer): + """Resize and quantize an image, then trace its ordered color layers.""" + + def __init__(self, img: Image.Image, color_count: int | None, timer: Timer) -> None: color_count = color_count or ColorSolver.DEFAULT_COLOR_COUNT color_count = max(color_count, ColorSolver.MIN_COLOR_COUNT) color_count = min(color_count, ColorSolver.MAX_COLOR_COUNT) @@ -21,7 +28,8 @@ def __init__(self, img, color_count, timer): self.timer = timer - def solve(self): + def solve(self) -> list[list[Path] | list[np.ndarray] | int]: + """Return paths, colors, width and height as a list.""" self.timer.start_timer("Quantization") labels, colors, has_background = quantize(self.img_arr, self.color_count) self.timer.end_timer() diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index a3bd234..5963217 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -1,41 +1,48 @@ +"""Quantize RGB colors while keeping transparent background pixels separate.""" + import cv2 import numpy as np -from PIL import Image -from faiss import Kmeans import scipy.ndimage as ndi +from faiss import Kmeans +from PIL import Image from skimage.measure import label BILATERAL_FILTER_DIAMETER = 7 BILATERAL_FILTER_SIGMA = 50 -# Applies a strong bilateral filter to the image. -# This greatly improves results for clip art. -# NOTE: photographs migh lose quite some detail due to this. + def bilateral_filter( - img_arr, - d = BILATERAL_FILTER_DIAMETER, - s = BILATERAL_FILTER_SIGMA -): + img_arr: np.ndarray, + d: int = BILATERAL_FILTER_DIAMETER, + s: float = BILATERAL_FILTER_SIGMA, +) -> np.ndarray: + """Smooth clip-art colors while preserving edges; photos may lose detail.""" return cv2.bilateralFilter(img_arr, d, s, s) -# First erodes a matrix, then dilates it -def dilate(matrix): + +def dilate(matrix: np.ndarray) -> np.ndarray: + """Dilate labels with a two-by-two kernel and OpenCV's default anchor.""" kernel = np.ones((2, 2)) return cv2.dilate(matrix, kernel) -# Fills holes (defined as cells that are zero) in a matrix -# By using the closes value found in the matrix that is not zero. -# See: https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.distance_transform_edt.html -def fill_holes(matrix): + +def fill_holes(matrix: np.ndarray) -> np.ndarray: + """Replace zero cells with their nearest nonzero value via a distance transform.""" closest = ndi.distance_transform_edt( - np.logical_not(matrix), - return_distances = False, - return_indices = True + np.logical_not(matrix), + return_distances=False, + return_indices=True, ) matrix = np.where(matrix != 0, matrix, matrix[closest[0], closest[1]]) return matrix -def enhance(img_arr, labels, colors): + +def enhance( + img_arr: np.ndarray, + labels: np.ndarray, + colors: np.ndarray, +) -> tuple[np.ndarray, np.ndarray]: + """Remove components mostly covered by neighboring colors, then fill holes.""" dims = img_arr.shape[:2] # 0 will be reserved for "unwritten" cells, or holes @@ -45,16 +52,13 @@ def enhance(img_arr, labels, colors): # Even though we don't allow it, technically the max # value in labels (before adding 1) is 255, so it's safer # to convert to uint16 to avoid overflows - np.where(labels == idx + 1, idx + 1, 0).astype(np.uint16) + np.where(labels == idx + 1, idx + 1, 0).astype(np.uint16) for idx, _ in enumerate(colors) ] # For each cluster, store a matrix of its connected components - # NOTE: see https://scikit-image.org/docs/stable/api/skimage.measure.html#skimage.measure.label - original_connected_components_list = [ - label(cluster) + 1 - for cluster in clusters - ] + # skimage's default connectivity includes diagonal neighbors. + original_connected_components_list = [label(cluster) + 1 for cluster in clusters] # Bincounts for each connected components matrix # Meaning bincount[i] = num_appearances(matrix, i) @@ -67,8 +71,7 @@ def enhance(img_arr, labels, colors): # Make a copy of the connected components # These will be modified and compared with the originals later connected_components_list = [ - np.array(item, copy = True) - for item in original_connected_components_list + np.array(item, copy=True) for item in original_connected_components_list ] for x, cluster_x in enumerate(clusters): @@ -86,32 +89,32 @@ def enhance(img_arr, labels, colors): connected_components_list[y] = np.where( overlap, 0, - connected_components_list[y] + connected_components_list[y], ) for x, connected_components in enumerate(connected_components_list): original_bincount = connected_components_bincounts[x] count = original_bincount.shape[0] - + new_bincount = np.bincount( - connected_components.flatten(), - minlength = count # Force same length + connected_components.flatten(), + minlength=count, # Force same length ) areas_ratio = np.divide( new_bincount.astype(np.float32), original_bincount.astype(np.float32), - out = np.ones((count, ), dtype = np.float32), - where = original_bincount != 0 + out=np.ones((count,), dtype=np.float32), + where=original_bincount != 0, ) # Update cluster # Connected components that lost more than 0.9 of their original area # are completely removed, others are kept clusters[x] = np.where( - areas_ratio[original_connected_components_list[x]] <= 0.1, - 0, - clusters[x] + areas_ratio[original_connected_components_list[x]] <= 0.1, + 0, + clusters[x], ) # Update labels with new cluster data @@ -123,24 +126,28 @@ def enhance(img_arr, labels, colors): labels = fill_holes(labels) return labels - 1, colors + # Try to get the cluster of pixels that represent a transparent background # If there is no transparent background, return None # This is needed because RGBA quantization is very volatile, and sometimes # opaque colors get assigned to the same clusters as highly transparent ones. # So we focus on the solid image + transparent background case for now. -def get_background_cluster(img_arr, t = 0.5): +def get_background_cluster(img_arr: np.ndarray, t: float = 0.5) -> np.ndarray | None: + """Return an alpha mask if any raw alpha is below t, otherwise return None.""" r, g, b, a = cv2.split(img_arr) - + has_transparent_background = np.any(a < t) if has_transparent_background: a = np.where(a / 255 < t, 1, 0) return np.reshape(a, img_arr.shape[:2]) - + return None + # Write the background cluster on top of a matrix of clusters (labels) # The background cluster has priority -def write_background_cluster(labels, bg_cluster): +def write_background_cluster(labels: np.ndarray, bg_cluster: np.ndarray) -> np.ndarray: + """Shift labels by one, reserving zero for the overriding background mask.""" labels = labels + 1 labels = np.where(bg_cluster > 0, 0, labels) return labels @@ -161,31 +168,37 @@ def get_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: return np.unique(palette[used_indices], axis=0) -def kmeans(img_arr, init_centroids): +def kmeans( + img_arr: np.ndarray, + init_centroids: np.ndarray, +) -> tuple[np.ndarray, np.ndarray]: + """Cluster RGB pixels with FAISS and return uint8 labels and centroids.""" channel_count = img_arr.shape[-1] data = np.reshape(img_arr, (-1, channel_count)).astype(np.float32) init_centroids = init_centroids.astype(np.float32) - km = Kmeans(channel_count, init_centroids.shape[0], niter = 100) - km.train(data, init_centroids = init_centroids) + km = Kmeans(channel_count, init_centroids.shape[0], niter=100) + km.train(data, init_centroids=init_centroids) _, labels = km.index.search(data, 1) return labels.astype(np.uint8), km.centroids.astype(np.uint8) - -def quantize(img_arr, color_count): + + +def quantize( + img_arr: np.ndarray, + color_count: int, +) -> tuple[np.ndarray, np.ndarray, bool]: + """Return cleaned labels, palette colors and whether a background was isolated.""" channel_count = img_arr.shape[-1] - + background_cluster = None if channel_count == 4: background_cluster = get_background_cluster(img_arr) img = Image.fromarray(img_arr) - img = img.convert('RGB') + img = img.convert("RGB") img_arr = np.asarray(img) img_arr = bilateral_filter(img_arr) - labels, colors = kmeans( - img_arr, - get_initial_centroids(img_arr, color_count) - ) + labels, colors = kmeans(img_arr, get_initial_centroids(img_arr, color_count)) labels = np.reshape(labels, img_arr.shape[:-1]) @@ -197,4 +210,4 @@ def quantize(img_arr, color_count): colors = colors.astype(np.uint8) labels, colors = enhance(img_arr, labels, colors) - return labels, colors, has_background \ No newline at end of file + return labels, colors, has_background diff --git a/vectorizing/svg/markup.py b/vectorizing/svg/markup.py index e44766a..643e7b6 100644 --- a/vectorizing/svg/markup.py +++ b/vectorizing/svg/markup.py @@ -1,62 +1,35 @@ -def truncate(number): - """ - Truncates a number to two decimal places. - We use this to limit the amount of decimal places used - in the final generated SVG markup (reduces file sizes). +"""Serialize traced paths without strokes or changes to their paint order.""" - Parameters: - number: The number to truncate. +from collections.abc import Iterable, Sequence - Returns: - The truncated number. - """ - return "{:.2f}".format(number) +import numpy as np +from pathops import Path -def to_SVG_color_string(color): - """ - Converts a color (represented as a tuple) to a valid - SVG color string. +def truncate(number: float) -> str: + """Format a coordinate with two decimal places to limit SVG size.""" + return f"{number:.2f}" - Parameters: - color: The input color. - Returns: - The SVG color string. - - Example: - to_SVG_color_string([20, 30, 40]) => rgb(20, 30, 40) - to_SVG_color_string([20, 30, 40, 0.5]) => rgba(20, 30, 40, 0.5) - - """ +def to_SVG_color_string(color: Sequence[float] | np.ndarray) -> str: + """Format RGB or RGBA components without scaling or rounding their values.""" func = "rgb" if len(color) == 3 else "rgba" tuple = "".join( [ f"{item}," if i != len(color) - 1 else f"{item}" for i, item in enumerate(color) - ] + ], ) return f"{func}({tuple})" -def generate_SVG_markup(compound_paths, colors, width, height): - """ - Generates SVG markup from a list of compound paths, - their respective colors, and the document dimensions. - - Parameters: - compound_paths: The compound path list (SKPath). - colors: Each compound path's color. - width: The width of the document. - height: The height of the document. - - Returns: - The SVG markup. - - Note: - compound paths are assumed to be made out of - only lines and cubic beziers. - """ +def generate_SVG_markup( + compound_paths: Iterable[Path], + colors: Iterable[Sequence[float] | np.ndarray], + width: int, + height: int, +) -> str: + """Serialize line/cubic paths in paint order, skipping empty geometry.""" paths_markup = [] for compound_path, color in zip(compound_paths, colors): @@ -89,7 +62,8 @@ def generate_SVG_markup(compound_paths, colors, width, height): paths_markup = "\n".join(paths_markup) return ( - f'\n' + f'\n' f"\n{paths_markup}\n\n" f"" ) diff --git a/vectorizing/tests/__init__.py b/vectorizing/tests/__init__.py index e69de29..2f3e1c1 100644 --- a/vectorizing/tests/__init__.py +++ b/vectorizing/tests/__init__.py @@ -0,0 +1 @@ +"""Regression checks for image vectorization and storage.""" diff --git a/vectorizing/tests/config.py b/vectorizing/tests/config.py index 871fff8..beeb78b 100644 --- a/vectorizing/tests/config.py +++ b/vectorizing/tests/config.py @@ -1,57 +1,36 @@ +"""Define image fixtures and solver settings for the integration gallery.""" + TESTS = { - '1px.jpg': [ - { - 'id': '1px_binary', - 'solver': 0 - }, - { - 'id': '1px_color', - 'solver': 1, - 'color_count': 9 - } + "1px.jpg": [ + {"id": "1px_binary", "solver": 0}, + {"id": "1px_color", "solver": 1, "color_count": 9}, ], - 'black_rectangle.png': [ + "black_rectangle.png": [ { - 'id': 'black_rectangle_binary', - 'solver': 0, + "id": "black_rectangle_binary", + "solver": 0, }, { - 'id': 'black_rectangle_color', - 'solver': 1, - 'color_count': 5, + "id": "black_rectangle_color", + "solver": 1, + "color_count": 5, }, ], - 'bubbles.png': [ - { - 'id': 'bubbles', - 'solver': 1, - 'color_count': 5 - } - ], - 'geo_logo.png': [ + "bubbles.png": [{"id": "bubbles", "solver": 1, "color_count": 5}], + "geo_logo.png": [ { - 'id': 'geo_logo', - 'solver': 0, + "id": "geo_logo", + "solver": 0, }, ], - 'shapes.png': [ - { - 'id': 'shapes', - 'solver': 1, - 'color_count': 4 - }, - ], - 'shapes_2.png': [ - { - 'id': 'shapes_2', - 'solver': 1, - 'color_count': 7 - } + "shapes.png": [ + {"id": "shapes", "solver": 1, "color_count": 4}, ], - 'white_text.png': [ + "shapes_2.png": [{"id": "shapes_2", "solver": 1, "color_count": 7}], + "white_text.png": [ { - 'id': 'white_text', - 'solver': 0, + "id": "white_text", + "solver": 0, }, ], -} \ No newline at end of file +} diff --git a/vectorizing/tests/conftest.py b/vectorizing/tests/conftest.py index 993f15c..64bafcd 100644 --- a/vectorizing/tests/conftest.py +++ b/vectorizing/tests/conftest.py @@ -1,12 +1,16 @@ +"""Provide an HTTP client isolated from the application's S3 bucket.""" + import os import pytest +from flask.testing import FlaskClient import vectorizing @pytest.fixture() -def client(monkeypatch): +def client(monkeypatch: pytest.MonkeyPatch) -> FlaskClient: + """Route test uploads to a required, separate bucket and enable Flask testing.""" test_bucket = os.getenv("S3_TEST_BUCKET") if not test_bucket: pytest.fail("S3_TEST_BUCKET must be set") diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py index 6dc3dd2..edd5e40 100644 --- a/vectorizing/tests/test.py +++ b/vectorizing/tests/test.py @@ -1,3 +1,5 @@ +"""Check image rendering, storage and exact color-optimization equivalence.""" + import os from io import BytesIO from pathlib import Path @@ -6,6 +8,7 @@ import numpy as np import pytest from cairosvg import svg2png +from flask.testing import FlaskClient from PIL import Image from vectorizing.geometry.bounds import compound_paths_bounds @@ -27,12 +30,8 @@ ) -def test(client): - """ - Tests all images inside /images directory using the TESTS object - in config.py - """ - +def test(client: FlaskClient) -> None: + """Render the configured gallery and compare or seed its local PNG baselines.""" results_path = Path(RESULTS_FOLDER_PATH) # Create results folder if non-existent @@ -79,7 +78,11 @@ def test(client): assert all([diff <= MAX_IMAGE_DIFFERENCE for diff in diffs]) -def test_write_img_difference_handles_rgba_baselines(tmp_path, monkeypatch): +def test_write_img_difference_handles_rgba_baselines( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Normalize transparent baseline pixels before computing RGB differences.""" baseline = tmp_path / "baseline.png" output = tmp_path / "difference.png" Image.new("RGBA", (2, 2), (0, 0, 0, 0)).save(baseline) @@ -94,7 +97,8 @@ def test_write_img_difference_handles_rgba_baselines(tmp_path, monkeypatch): assert output.exists() -def test_color_solver_preserves_empty_transparent_image(): +def test_color_solver_preserves_empty_transparent_image() -> None: + """Keep every rendered pixel transparent for an empty input image.""" image = Image.open(Path(__file__).parent / "images" / "empty.png") paths, colors, width, height = ColorSolver(image, 6, Timer()).solve() markup = generate_SVG_markup(paths, colors, width, height) @@ -319,7 +323,8 @@ def test_color_optimizations_preserve_vectorization( ) -def test_uploads_markup_to_s3(client): +def test_uploads_markup_to_s3(client: FlaskClient) -> None: + """Store the generated SVG with its media type and return the object's key.""" response = client.post( "/", json={ diff --git a/vectorizing/tests/test_api_contracts.py b/vectorizing/tests/test_api_contracts.py new file mode 100644 index 0000000..4c050c3 --- /dev/null +++ b/vectorizing/tests/test_api_contracts.py @@ -0,0 +1,116 @@ +"""Preserve argument validation and raw/error HTTP response contracts.""" + +from types import SimpleNamespace +from unittest.mock import Mock + +import pytest +from flask.testing import FlaskClient +from PIL import Image + +import vectorizing + + +@pytest.mark.parametrize( + "payload", + [ + {}, + {"solver": 0}, + {"url": "image", "solver": 2}, + {"url": "image", "solver": "1"}, + {"url": "image", "crop_box": [0, 0, 3]}, + {"url": "image", "crop_box": [0, 0, 3.5, 4]}, + ], +) +def test_invalid_arguments_return_the_same_error( + payload: dict[str, object], + client: FlaskClient, +) -> None: + """Keep rejected inputs false and return the established 400 JSON response.""" + assert vectorizing.validate_args(payload) is False + response = client.post("/", json=payload) + assert response.status_code == 400 + assert response.get_json() == {"success": False, "error": "INVALID_PARAMETERS"} + + +@pytest.mark.parametrize( + "payload", + [ + {"url": "image"}, + {"url": None}, + {"url": "image", "solver": True}, + {"url": "image", "crop_box": []}, + {"url": "image", "crop_box": [True, 0, 3, 4]}, + ], +) +def test_argument_validation_preserves_accepted_values( + payload: dict[str, object], +) -> None: + """Preserve presence-only URL checks, falsey crop boxes and integer booleans.""" + result = vectorizing.validate_args(payload) + assert isinstance(result, SimpleNamespace) + assert vars(result) == { + "url": payload["url"], + "solver": payload.get("solver", 0), + "crop_box": payload.get("crop_box"), + "raw": None, + "color_count": None, + } + + +@pytest.mark.parametrize("solver", [0, 1]) +def test_raw_requests_crop_before_vectorizing_and_do_not_upload( + solver: int, + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep raw responses as SVG bytes and preserve crop ordering for both solvers.""" + image = Image.new("RGB", (8, 8), (40, 50, 60)) + load = Mock(return_value=image) + binary = Mock(wraps=vectorizing.process_binary) + color = Mock(wraps=vectorizing.process_color) + upload = Mock() + monkeypatch.setattr(vectorizing, "try_read_image_from_url", load) + monkeypatch.setattr(vectorizing, "process_binary", binary) + monkeypatch.setattr(vectorizing, "process_color", color) + monkeypatch.setattr(vectorizing, "upload_markup", upload) + response = client.post( + "/", + json={ + "url": "image", + "solver": solver, + "color_count": 2, + "crop_box": [0, 1, 4, 5], + "raw": True, + }, + ) + assert response.status_code == 200 + assert response.data.startswith(b" None: + """Return the established 500 payload when image processing raises an error.""" + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(side_effect=ValueError("bad image")), + ) + response = client.post("/", json={"url": "image"}) + assert response.status_code == 500 + assert response.get_json() == {"success": False, "error": "INTERNAL_SERVER_ERROR"} + + +def test_health_response(client: FlaskClient) -> None: + """Keep the health endpoint's status and JSON payload stable.""" + response = client.get("/health") + assert response.status_code == 200 + assert response.get_json() == {"success": True} diff --git a/vectorizing/tests/test_image_reading.py b/vectorizing/tests/test_image_reading.py new file mode 100644 index 0000000..cf4a009 --- /dev/null +++ b/vectorizing/tests/test_image_reading.py @@ -0,0 +1,116 @@ +"""Preserve image modes, request options and public loading-error behavior.""" + +from io import BytesIO +from pathlib import Path +from types import SimpleNamespace +from unittest.mock import Mock + +import pytest +from PIL import Image + +from vectorizing.util import read + + +@pytest.mark.parametrize( + "mode, expected_mode", + [ + ("RGB", "RGB"), + ("RGBA", "RGBA"), + ("1", "RGB"), + ("L", "RGB"), + ("P", "RGBA"), + ("PA", "RGBA"), + ], +) +def test_supported_image_modes(mode: str, expected_mode: str) -> None: + """Keep RGB/RGBA identity and preserve pixels when converting other modes.""" + image = Image.new(mode, (8, 8)) + actual = read.convert_RGB_A(image) + assert actual.mode == expected_mode + assert actual.tobytes() == image.convert(expected_mode).tobytes() + if mode in {"RGB", "RGBA"}: + assert actual is image + + +@pytest.mark.parametrize("reader", ["path", "url"]) +@pytest.mark.parametrize( + "exception_type", + [OSError, ValueError, MemoryError, KeyboardInterrupt, SystemExit], +) +def test_loading_failures_keep_the_public_wrapper( + reader: str, + exception_type: type[BaseException], + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Retain catch-all wrapping, original context and the public exception args.""" + cause = exception_type("loading failed") + if reader == "path": + monkeypatch.setattr(read.Image, "open", Mock(side_effect=cause)) + loader, error_type = read.try_read_image_from_path, read.PathReadError + message = "Failed to read image from provided path." + else: + monkeypatch.setattr(read.requests, "get", Mock(side_effect=cause)) + loader, error_type = read.try_read_image_from_url, read.URLReadError + message = "Failed to read image from provided URL." + with pytest.raises(error_type) as caught: + loader("source") + assert caught.value.args == (caught.value, message) + assert caught.value.__context__ is cause + assert not caught.value.__suppress_context__ + + +@pytest.mark.parametrize("reader", ["path", "url"]) +def test_unsupported_modes_are_not_wrapped_as_loading_errors( + reader: str, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Leave mode conversion outside the image-loading exception wrapper.""" + monkeypatch.setattr( + read.Image, + "open", + Mock(return_value=Image.new("CMYK", (8, 8))), + ) + monkeypatch.setattr( + read.requests, + "get", + Mock(return_value=SimpleNamespace(content=b"")), + ) + loader = ( + read.try_read_image_from_path + if reader == "path" + else read.try_read_image_from_url + ) + with pytest.raises(read.ImageFormatError): + loader("source") + + +@pytest.mark.parametrize("status_code", [200, 404]) +def test_url_reader_preserves_request_and_decoding_contract( + status_code: int, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Send the service user agent and decode images regardless of HTTP status.""" + image = Image.new("RGBA", (8, 8), (20, 30, 40, 128)) + encoded = BytesIO() + image.save(encoded, format="PNG") + get = Mock( + return_value=SimpleNamespace( + content=encoded.getvalue(), + status_code=status_code, + ), + ) + monkeypatch.setattr(read.requests, "get", get) + url = "https://example.invalid/image.png?signature=fixture" + actual = read.try_read_image_from_url(url) + get.assert_called_once_with(url, headers={"User-Agent": "KittlVectorizing/1.0.0"}) + assert actual.mode == "RGBA" + assert actual.tobytes() == image.tobytes() + + +def test_path_reader_accepts_path_objects(tmp_path: Path) -> None: + """Read Path objects and normalize grayscale pixels to RGB.""" + path = tmp_path / "gray.png" + Image.new("L", (8, 8), 64).save(path) + actual = read.try_read_image_from_path(path) + assert actual.mode == "RGB" + assert actual.getpixel((0, 0)) == (64, 64, 64) diff --git a/vectorizing/tests/test_svg_markup.py b/vectorizing/tests/test_svg_markup.py new file mode 100644 index 0000000..31e2e80 --- /dev/null +++ b/vectorizing/tests/test_svg_markup.py @@ -0,0 +1,76 @@ +"""Freeze externally visible SVG formatting, including whitespace and alpha.""" + +from collections.abc import Sequence + +import numpy as np +import pytest +from pathops import Path + +from vectorizing.svg.markup import generate_SVG_markup, to_SVG_color_string, truncate + + +@pytest.mark.parametrize( + "number, expected", + [ + (0.0, "0.00"), + (-0.0, "-0.00"), + (1.234, "1.23"), + (1.236, "1.24"), + (2.675, "2.67"), + (float("inf"), "inf"), + (float("-inf"), "-inf"), + (float("nan"), "nan"), + ], +) +def test_coordinate_formatting(number: float, expected: str) -> None: + """Retain Python's two-decimal formatting rather than truncating coordinates.""" + assert truncate(number) == expected + + +@pytest.mark.parametrize( + "color, expected", + [ + ([20, 30, 40], "rgb(20,30,40)"), + ([20, 30, 40, 0.5], "rgba(20,30,40,0.5)"), + ([20, 30, 40, 0], "rgba(20,30,40,0)"), + (np.array([20, 30, 40, 0.5]), "rgba(20.0,30.0,40.0,0.5)"), + ], +) +def test_color_formatting(color: Sequence[float] | np.ndarray, expected: str) -> None: + """Preserve component representations without scaling alpha or adding spaces.""" + assert to_SVG_color_string(color) == expected + + +def test_svg_serialization_preserves_exact_markup() -> None: + """Keep paint order, empty-path filtering, cubic syntax and document whitespace.""" + curve = Path() + curve.moveTo(0, 0) + curve.lineTo(10, 0) + curve.cubicTo(10, 1, 9, 2, 0, 0) + curve.close() + overlay = Path() + overlay.moveTo(1, 1) + overlay.lineTo(2, 2) + overlay.close() + actual = generate_SVG_markup( + [Path(), curve, overlay], + [[255, 255, 255], [20, 30, 40], [50, 60, 70, 0.5]], + 40, + 20, + ) + assert actual == ( + '\n' + '\n\n' + '\n' + "\n" + ) + + +def test_empty_svg_serialization() -> None: + """Keep the empty document's dimensions and blank group unchanged.""" + assert generate_SVG_markup([], [], 8, 9) == ( + '\n\n\n\n' + ) diff --git a/vectorizing/tests/testutil.py b/vectorizing/tests/testutil.py index 11ab5a6..6539a24 100644 --- a/vectorizing/tests/testutil.py +++ b/vectorizing/tests/testutil.py @@ -1,7 +1,10 @@ +"""Support the image gallery with S3 fixtures and RGB difference images.""" + from pathlib import Path import cv2 import numpy as np +from flask.testing import FlaskClient from PIL import Image from sewar.full_ref import uqi @@ -22,22 +25,8 @@ DIFF_OUTPUT_FOLDER_PATH = TESTS_FOLDER_PATH / "diff_output" -def get_image_url(img_name): - """ - Gets an image URL. Uploads it to the S3 testing bucket, - if not there already - - Parameters - ---------- - img_name : string - The name of the image. It is used as key for the upload. - - Returns - ------- - str - The URL of the image in the S3 bucket - """ - +def get_image_url(img_name: str) -> str | None: + """Return a fixture's S3 URL, uploading the fixture if it is not present.""" object_url = get_object_url(img_name, S3_TEST_BUCKET) if object_url: @@ -46,24 +35,12 @@ def get_image_url(img_name): return upload_file(IMAGES_FOLDER_PATH / img_name, S3_TEST_BUCKET, img_name) -def get_markup(client, img_name, request_params): - """ - Vectorizes an image and returns the SVG markup - - Parameters - ---------- - client : Flask - A flask test client - img_name: string - The name of the image - request_params: - Parameters for the vectorize request - - Returns - ------- - str - SVG markup - """ +def get_markup( + client: FlaskClient, + img_name: str, + request_params: dict[str, object], +) -> bytes: + """Vectorize an S3 fixture through the HTTP API and return raw response bytes.""" image_url = get_image_url(img_name) request_params = { @@ -75,26 +52,12 @@ def get_markup(client, img_name, request_params): return client.post("/", json=request_params).data -def compute_img_difference(img, expected_img_path, small_image_test_factor=0.1): - """ - Computes difference between two images using UQI - - Parameters - ---------- - img : PIL.Image - An image - expected_img_path: - A path to a baseline image to compare [img] with - - Both images are assumed to have the same size - - Returns - ------- - float - A number between 0 and 1. - 0 means equal - 1 means completely different - """ +def compute_img_difference( + img: Image.Image, + expected_img_path: Path, + small_image_test_factor: float = 0.1, +) -> float: + """Compare equal-sized RGB images with UQI or a small-image pixel threshold.""" expected_img = try_read_image_from_path(expected_img_path).convert("RGB") expected_img_arr = np.asarray(expected_img).astype(np.uint8) img_arr = np.asarray(img.convert("RGB")).astype(np.uint8) @@ -104,8 +67,7 @@ def compute_img_difference(img, expected_img_path, small_image_test_factor=0.1): if px_count <= MIN_UQI_PIXEL_COUNT: # For very small images, uqi sometimes returns nan - # We then use a simple metric for these cases, we also don't particularly care too - # much about such small images + # Use a pixel-count threshold instead of UQI for these small images. diff = img_arr - expected_img_arr norm = np.linalg.norm(diff, axis=2) @@ -128,26 +90,8 @@ def compute_img_difference(img, expected_img_path, small_image_test_factor=0.1): return 1 - image_quality_index -def convert_to_RGBGray(img_arr): - """ - Converts an image's colors to grayscale, and returns it - in RGB format. This is useful because to write image diffs, - we display the baseline image in gray to be able to have an - always-contrasting highlight color. - - This highlight color shouldn't be a shade of gray though, - so a luminance image is not enough. RGB is needed. - - Parameters - ---------- - img_arr : np.array - An image array - - Returns - ------- - np.array - The converted image - """ +def convert_to_RGBGray(img_arr: np.ndarray) -> np.ndarray: + """Return RGB grayscale pixels, compositing RGBA inputs over white.""" if img_arr.shape[-1] == 4: img_arr = alpha_blend(img_arr) img_arr = cv2.cvtColor(img_arr, cv2.COLOR_RGB2GRAY) @@ -155,19 +99,12 @@ def convert_to_RGBGray(img_arr): return img_arr -def write_img_difference(predicted_img, expected_img_path, output_name): - """ - Writes difference between two images to /diff_output - - Parameters - ---------- - predicted_img : PIL.Image - The predicted image - expected_img_path: string - A path to the expected, or baseline, image - output_name: - The name of the file to be placed in diff_output - """ +def write_img_difference( + predicted_img: Image.Image, + expected_img_path: Path, + output_name: str, +) -> None: + """Write a grayscale baseline with red highlights proportional to pixel error.""" expected_img = try_read_image_from_path(expected_img_path).convert("RGB") predicted_img_arr = np.asarray(predicted_img.convert("RGB")).astype(np.uint8) diff --git a/vectorizing/util/limit_size.py b/vectorizing/util/limit_size.py index 586c6a5..1823e11 100644 --- a/vectorizing/util/limit_size.py +++ b/vectorizing/util/limit_size.py @@ -1,11 +1,16 @@ +"""Bound image area while preserving the source aspect ratio.""" + import math + from PIL import Image # Size restrictions for image MIN_PIXEL_COUNT = 64 -MAX_PIXEL_COUNT = 1024 ** 2 +MAX_PIXEL_COUNT = 1024**2 + -def resize_to_target(img, target_pixel_count): +def resize_to_target(img: Image.Image, target_pixel_count: int) -> Image.Image: + """Resize with Lanczos to rounded dimensions near the requested pixel count.""" width = img.size[0] height = img.size[1] @@ -14,15 +19,17 @@ def resize_to_target(img, target_pixel_count): k = math.sqrt(target_pixel_count / (width * height)) target_width = round(k * width) target_height = round(k * height) - return img.resize((target_width, target_height), resample = Image.Resampling.LANCZOS) + return img.resize((target_width, target_height), resample=Image.Resampling.LANCZOS) -def limit_size(img): + +def limit_size(img: Image.Image) -> Image.Image: + """Resize images outside the area limits; otherwise return the original image.""" pixel_count = img.size[0] * img.size[1] if pixel_count < MIN_PIXEL_COUNT: return resize_to_target(img, MIN_PIXEL_COUNT) - + if pixel_count > MAX_PIXEL_COUNT: return resize_to_target(img, MAX_PIXEL_COUNT) - - return img \ No newline at end of file + + return img diff --git a/vectorizing/util/read.py b/vectorizing/util/read.py index 54edea1..7a84dfa 100644 --- a/vectorizing/util/read.py +++ b/vectorizing/util/read.py @@ -1,52 +1,73 @@ -import math +"""Read supported raster formats and normalize their color modes.""" + +from io import BytesIO +from os import PathLike + import requests -import numpy as np from PIL import Image -from io import BytesIO MIN_PIXEL_COUNT = 64 -MAX_PIXEL_COUNT = 1024 ** 2 -SMALL_PIXEL_COUNT = 512 ** 2 +MAX_PIXEL_COUNT = 1024**2 +SMALL_PIXEL_COUNT = 512**2 + + +class URLReadError(Exception): + """Wrap failures while downloading or opening an image URL.""" + + def __init__(self) -> None: + super().__init__(self, "Failed to read image from provided URL.") + -class URLReadError (Exception): - def __init__ (self): - super().__init__(self, 'Failed to read image from provided URL.') +class PathReadError(Exception): + """Wrap failures while opening a local image.""" -class PathReadError (Exception): - def __init__ (self): - super().__init__(self, 'Failed to read image from provided path.') + def __init__(self) -> None: + super().__init__(self, "Failed to read image from provided path.") -class ImageFormatError (Exception): - def __init__(self): - super().__init__(self, 'Image format not supported.') -def convert_RGB_A(img): - if img.mode == 'RGB' or img.mode == 'RGBA': +class ImageFormatError(Exception): + """Signal an unsupported image color mode.""" + + def __init__(self) -> None: + super().__init__(self, "Image format not supported.") + + +def convert_RGB_A(img: Image.Image) -> Image.Image: + """Keep RGB/RGBA images unchanged and convert supported grayscale/palette modes.""" + if img.mode == "RGB" or img.mode == "RGBA": return img - + map = { - '1': 'RGB', - 'L': 'RGB', - 'P': 'RGBA', - 'PA': 'RGBA', + "1": "RGB", + "L": "RGB", + "P": "RGBA", + "PA": "RGBA", } - if not img.mode in map: + if img.mode not in map: raise ImageFormatError() - + return img.convert(map.get(img.mode)) -def try_read_image_from_path(path): + +def try_read_image_from_path(path: str | PathLike[str]) -> Image.Image: + """Open an image, wrapping all loading exceptions including interrupts.""" try: img = Image.open(path) - except: + except BaseException: # noqa: B036 - All loading failures use the public wrapper. raise PathReadError() return convert_RGB_A(img) -def try_read_image_from_url(url): + +def try_read_image_from_url(url: str) -> Image.Image: + """Download without a time limit, wrapping all loading exceptions.""" try: - resp = requests.get(url, headers={"User-Agent": "KittlVectorizing/1.0.0"}) + # Image downloads wait without a timeout. + resp = requests.get( # noqa: S113 + url, + headers={"User-Agent": "KittlVectorizing/1.0.0"}, + ) img = Image.open(BytesIO(resp.content)) - except: + except BaseException: # noqa: B036 - All loading failures use the public wrapper. raise URLReadError() - return convert_RGB_A(img) \ No newline at end of file + return convert_RGB_A(img) From 279960d31018c99586b1bd4727c9cd307035f8f4 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 14:58:57 +0200 Subject: [PATCH 08/16] chore(dev): add output comparison and benchmark tools (#80) --- .dockerignore | 3 + .gitignore | 1 + README.md | 33 ++ scripts/__init__.py | 1 + scripts/_vectorization.py | 143 ++++++++ scripts/benchmark_vectorization.py | 214 ++++++++++++ scripts/vectorization_outputs.py | 181 ++++++++++ vectorizing/tests/test_developer_tools.py | 406 ++++++++++++++++++++++ 8 files changed, 982 insertions(+) create mode 100644 scripts/__init__.py create mode 100644 scripts/_vectorization.py create mode 100644 scripts/benchmark_vectorization.py create mode 100644 scripts/vectorization_outputs.py create mode 100644 vectorizing/tests/test_developer_tools.py diff --git a/.dockerignore b/.dockerignore index 9cc1876..c37dcdd 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,3 +1,6 @@ +# Local reports, captures and scratch files +.user/ + ### Python template # Byte-compiled / optimized / DLL files __pycache__/ diff --git a/.gitignore b/.gitignore index 1b2aedb..04497c6 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +/.user/ __pycache__ .pytest_cache .DS_Store diff --git a/README.md b/README.md index 1946d65..b2e2bc0 100644 --- a/README.md +++ b/README.md @@ -53,6 +53,39 @@ pre-commit run --all-files The first execution might take a bit longer, as it will set up the virtual environment where the linter and the formatter will run. +## Output comparisons and benchmarks + +These developer commands use local fixtures and need no AWS credentials or Moto. +Run them in the dev container or an environment with `requirements/dev.txt` and +its system libraries installed. They do not change application code or dependencies. + +Capture each version into a different directory, then compare: + +```bash +python scripts/vectorization_outputs.py capture .user/before --source-root /path/to/baseline +python scripts/vectorization_outputs.py capture .user/after +python scripts/vectorization_outputs.py compare .user/before .user/after +python scripts/benchmark_vectorization.py --output .user/benchmark.json --case aftermath-16 +``` + +- Repeat `--case` to select fixtures; `--help` lists them. The default is all 15 cases. +- Comparison checks SVG bytes, decoded RGBA pixels, colors, dimensions, bounds and input identity. Exit codes: `0` equal, `1` changed, `2` invalid/incomplete artifacts. Nonempty output directories and existing benchmark reports are never overwritten. +- Benchmark timing covers the solver, SVG serialization and bounds, not file decoding, HTTP/S3 or rasterization. Each sample uses a fresh process; peak RSS includes imports, input preparation, warmups and output checks. Linux and macOS memory units are normalized to MiB. +- Add `--baseline-root /path/to/baseline` to benchmark two trusted checkouts in alternating order, with exact-output checks. `--repeats` defaults to 3 and `--warmups` to 1 per process. Output mismatches exit `1` but still save the report; timings have no pass/fail threshold. +- Reports include runtime/source fingerprints and raw samples. `--label` can record commit IDs. Checkouts share the installed dependencies; this is not a dependency-isolated or production/concurrency benchmark. Use only trusted source roots. + +For Docker, build the current scripts and mount only the output directory: + +```bash +mkdir -p .user +docker build -t vectorizing:tools . +docker run --rm --user "$(id -u):$(id -g)" -v "$PWD/.user:/results" vectorizing:tools \ + python scripts/vectorization_outputs.py capture /results/candidate +``` + +A separate baseline checkout must also be mounted when using `--source-root` or +`--baseline-root`. Generated artifacts under `.user/` are excluded from Git and Docker builds. + ## Server The server has a single endpoint that receives `POST` requests. diff --git a/scripts/__init__.py b/scripts/__init__.py new file mode 100644 index 0000000..fa849dd --- /dev/null +++ b/scripts/__init__.py @@ -0,0 +1 @@ +"""Local development and maintenance commands.""" diff --git a/scripts/_vectorization.py b/scripts/_vectorization.py new file mode 100644 index 0000000..cd8941b --- /dev/null +++ b/scripts/_vectorization.py @@ -0,0 +1,143 @@ +"""Shared fixtures and offline solver execution for developer commands.""" + +import hashlib +import math +import os +import platform +import sys +from collections.abc import Callable +from importlib.metadata import version +from pathlib import Path + +ROOT = Path(__file__).resolve().parents[1] +# Explicit cases keep developer reports independent of pytest's module layout. +CASES = { + "1px_binary": ("1px.jpg", "binary", None), + "1px_color": ("1px.jpg", "color", 9), + "black_rectangle_binary": ("black_rectangle.png", "binary", None), + "black_rectangle_color": ("black_rectangle.png", "color", 5), + "bubbles": ("bubbles.png", "color", 5), + "geo_logo": ("geo_logo.png", "binary", None), + "shapes": ("shapes.png", "color", 4), + "shapes_2": ("shapes_2.png", "color", 7), + "white_text": ("white_text.png", "binary", None), + "aftermath-2": ("aftermath.png", "color", 2), + "aftermath-6": ("aftermath.png", "color", 6), + "aftermath-16": ("aftermath.png", "color", 16), + "aftermath-64": ("aftermath.png", "color", 64), + "empty-binary": ("empty.png", "binary", None), + "empty-color": ("empty.png", "color", 6), +} + + +def file_hash(path: Path) -> str: + """Hash file bytes without retaining the entire file in memory.""" + with path.open("rb") as source: + return hashlib.file_digest(source, "sha256").hexdigest() + + +def fingerprint(svg: str, details: dict[str, object]) -> dict[str, object]: + """Record exact SVG bytes alongside palette, dimensions, bounds and input.""" + return {"svg_sha256": hashlib.sha256(svg.encode("utf-8")).hexdigest(), **details} + + +def source_hash(source_root: Path) -> str: + """Fingerprint runtime Python sources without requiring Git in the container.""" + digest = hashlib.sha256() + for path in sorted((source_root / "vectorizing").rglob("*.py")): + relative = path.relative_to(source_root) + if "tests" not in relative.parts: + digest.update(str(relative).replace(os.sep, "/").encode("utf-8") + b"\0") + digest.update(path.read_bytes() + b"\0") + return digest.hexdigest() + + +def environment() -> dict[str, object]: + """Report the numerical runtime and native thread counts without credentials.""" + import cv2 + import faiss + + packages = ( + "numpy", + "Pillow", + "scipy", + "scikit-image", + "faiss-cpu", + "opencv-python-headless", + "pypotrace", + "skia-pathops", + "CairoSVG", + ) + return { + "python": platform.python_version(), + "platform": platform.platform(), + "machine": platform.machine(), + "cpus": os.cpu_count(), + "faiss_threads": faiss.omp_get_max_threads(), + "opencv_threads": cv2.getNumThreads(), + "versions": {name: version(name) for name in packages}, + } + + +def prepare_case( + name: str, + source_root: Path, +) -> Callable[[], tuple[str, dict[str, object]]]: + """Load a fixture once and return a fresh solver/SVG/bounds run for its checkout.""" + source_root = source_root.resolve() + if not (source_root / "vectorizing" / "__init__.py").is_file(): + raise ValueError(f"Not a vectorizing checkout: {source_root}") + sys.path.insert(0, str(source_root)) + # Package imports require these settings; no server or S3 client is created. + os.environ.setdefault("PORT", "8000") + os.environ.setdefault("S3_BUCKET", "unused-vectorization-tools") + + import numpy as np + from PIL import Image + + import vectorizing + from vectorizing.geometry.bounds import compound_paths_bounds + from vectorizing.server.timer import Timer + from vectorizing.solvers.binary.BinarySolver import BinarySolver + from vectorizing.solvers.color.ColorSolver import ColorSolver + from vectorizing.svg.markup import generate_SVG_markup + from vectorizing.util.read import convert_RGB_A + + if Path(vectorizing.__file__).resolve().parent != source_root / "vectorizing": + raise ValueError( + "A different checkout is already imported; use a fresh process", + ) + filename, solver, count = CASES[name] + path = source_root / "vectorizing" / "tests" / "images" / filename + with Image.open(path) as source: + image = convert_RGB_A(source).copy() + source_info = { + "image": filename, + "sha256": file_hash(path), + "solver": solver, + "color_count": count, + } + + def run() -> tuple[str, dict[str, object]]: + result = ( + BinarySolver(image).solve() + if solver == "binary" + else ColorSolver(image, count, Timer()).solve() + ) + paths, colors, width, height = result + bounds = compound_paths_bounds(paths) + # Empty artwork has infinite bounds; strings keep the report valid JSON. + bounds = { + key: float(value) if math.isfinite(value) else str(float(value)) + for key, value in bounds.items() + } + palette = np.asarray(colors) + return generate_SVG_markup(*result), { + "input": source_info, + "colors": palette.tolist(), + "colors_dtype": str(palette.dtype), + "dimensions": [width, height], + "bounds": bounds, + } + + return run diff --git a/scripts/benchmark_vectorization.py b/scripts/benchmark_vectorization.py new file mode 100644 index 0000000..00fdd06 --- /dev/null +++ b/scripts/benchmark_vectorization.py @@ -0,0 +1,214 @@ +"""Measure offline solver/SVG/bounds time and fresh-process peak memory.""" + +import argparse +import json +import os +import statistics +import subprocess # noqa: S404 - Only the fixed Python worker is launched. +import sys +import time +from pathlib import Path + + +def peak_rss_mib() -> float: + """Convert the process high-water mark to MiB on Linux and macOS.""" + if sys.platform != "darwin" and not sys.platform.startswith("linux"): + raise ValueError("Peak RSS measurement supports Linux and macOS only") + import resource + + value = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss + return value / (1024 * 1024 if sys.platform == "darwin" else 1024) + + +def sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: + """Warm one case, time one run and verify stable output in this fresh process.""" + from scripts._vectorization import ( + environment, + fingerprint, + prepare_case, + source_hash, + ) + + run = prepare_case(name, source_root) + revision = source_hash(source_root) + expected = None + consistent = True + for _ in range(warmups + 1): + start = time.perf_counter() + svg, details = run() + elapsed = (time.perf_counter() - start) * 1000 + output = fingerprint(svg, details) + if expected is not None and expected != output: + consistent = False + expected = output + runtime = environment() + return { + "elapsed_ms": elapsed, + "peak_rss_mib": peak_rss_mib(), + "output": output, + "consistent": consistent, + "environment": runtime, + "pid": os.getpid(), + "source_sha256": revision, + } + + +def run_sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: + """Run this script in a new interpreter, propagating worker failures.""" + command = [ + sys.executable, + str(Path(__file__).resolve()), + "--worker", + "--case", + name, + "--source-root", + str(source_root), + "--warmups", + str(warmups), + ] + # The executable and script are fixed; arguments are passed without a shell. + result = subprocess.run(command, capture_output=True, text=True) # noqa: S603 + if result.returncode: + raise RuntimeError( + f"Benchmark worker failed for {name}: {result.stderr.strip()}", + ) + return json.loads(result.stdout) + + +def benchmark( + names: list[str], + roots: dict[str, Path], + repeats: int, + warmups: int, +) -> tuple[dict[str, object], bool]: + """Alternate variants, retaining raw samples and exact-output equality checks.""" + cases = {} + all_equal = True + for name in names: + samples = {variant: [] for variant in roots} + for iteration in range(repeats): + order = list(roots) if iteration % 2 == 0 else list(reversed(roots)) + for variant in order: + samples[variant].append(run_sample(name, roots[variant], warmups)) + reference = next(iter(samples.values()))[0]["output"] + equal = all( + row["consistent"] and row["output"] == reference + for rows in samples.values() + for row in rows + ) + all_equal &= equal + medians = { + variant: { + "elapsed_ms": statistics.median(row["elapsed_ms"] for row in rows), + "peak_rss_mib": statistics.median(row["peak_rss_mib"] for row in rows), + } + for variant, rows in samples.items() + } + cases[name] = {"samples": samples, "medians": medians, "outputs_equal": equal} + for variant, values in medians.items(): + print( + f"{name} {variant}: {values['elapsed_ms']:.2f} ms, " + f"{values['peak_rss_mib']:.2f} MiB", + ) + if not equal: + print( + f"{name}: outputs differ; timings are not an equivalent comparison.", + file=sys.stderr, + ) + return cases, all_equal + + +def positive(value: str) -> int: + """Require at least one measured sample.""" + count = int(value) + if count < 1: + raise argparse.ArgumentTypeError("must be at least 1") + return count + + +def nonnegative(value: str) -> int: + """Allow zero warmups, but reject negative counts.""" + count = int(value) + if count < 0: + raise argparse.ArgumentTypeError("must be at least 0") + return count + + +def main(argv: list[str] | None = None) -> int: + """Write a benchmark report, returning one when any outputs differ.""" + from scripts._vectorization import CASES, ROOT + + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--output", type=Path, help="New JSON report path (required)") + parser.add_argument( + "--source-root", + type=Path, + default=ROOT, + help="Trusted candidate checkout", + ) + parser.add_argument( + "--baseline-root", + type=Path, + help="Optional trusted baseline checkout", + ) + parser.add_argument( + "--case", + action="append", + choices=CASES, + help="Repeat to select cases; default: all", + ) + parser.add_argument("--repeats", type=positive, default=3) + parser.add_argument( + "--warmups", + type=nonnegative, + default=1, + help="Warmups per fresh process", + ) + parser.add_argument( + "--label", + help="Optional revisions or description for this report", + ) + parser.add_argument("--worker", action="store_true", help=argparse.SUPPRESS) + args = parser.parse_args(argv) + names = list(dict.fromkeys(args.case or CASES)) + try: + if args.worker: + if len(names) != 1: + raise ValueError("A worker measures exactly one case") + print( + json.dumps( + sample(names[0], args.source_root, args.warmups), + allow_nan=False, + ), + ) + return 0 + if args.output is None: + raise ValueError("--output is required") + if args.output.exists(): + raise ValueError(f"Refusing to overwrite: {args.output}") + roots = {"baseline": args.baseline_root.resolve()} if args.baseline_root else {} + roots["candidate"] = args.source_root.resolve() + cases, equal = benchmark(names, roots, args.repeats, args.warmups) + report = { + "schema_version": 1, + "label": args.label, + "source_roots": {name: str(path) for name, path in roots.items()}, + "repeats": args.repeats, + "warmups_per_process": args.warmups, + "timing_scope": "solver, SVG serialization, colors, dimensions and bounds", + "rss_scope": "fresh process: imports, input, warmups, output checks", + "cases": cases, + "outputs_equal": equal, + } + args.output.parent.mkdir(parents=True, exist_ok=True) + with args.output.open("x", encoding="utf-8") as destination: + json.dump(report, destination, indent=2, sort_keys=True, allow_nan=False) + destination.write("\n") + return int(not equal) + except (OSError, ValueError, RuntimeError, ImportError) as error: + parser.error(str(error)) + + +if __name__ == "__main__": + sys.path.insert(0, str(Path(__file__).resolve().parents[1])) + raise SystemExit(main()) diff --git a/scripts/vectorization_outputs.py b/scripts/vectorization_outputs.py new file mode 100644 index 0000000..1b86e0d --- /dev/null +++ b/scripts/vectorization_outputs.py @@ -0,0 +1,181 @@ +"""Capture local fixtures and compare exact SVG, pixel and solver outputs.""" + +import argparse +import hashlib +import json +import sys +from pathlib import Path + + +def capture( + output: Path, + names: list[str], + source_root: Path, + label: str | None, +) -> None: + """Write a complete manifest last, refusing to replace existing artifacts.""" + from cairosvg import svg2png + + from scripts._vectorization import ( + environment, + fingerprint, + prepare_case, + source_hash, + ) + + if output.exists() and (not output.is_dir() or any(output.iterdir())): + raise ValueError(f"Output must be a new or empty directory: {output}") + output.mkdir(parents=True, exist_ok=True) + cases = {} + for name in names: + svg, details = prepare_case(name, source_root)() + svg_bytes = svg.encode("utf-8") + for extension, data in { + "svg": svg_bytes, + "png": svg2png(bytestring=svg_bytes), + }.items(): + with (output / f"{name}.{extension}").open("xb") as artifact: + artifact.write(data) + pixel_hash, shape = pixels(output / f"{name}.png") + cases[name] = { + **fingerprint(svg, details), + "rgba_sha256": pixel_hash, + "rgba_shape": shape, + } + print(f"Captured {name}") + report = { + "schema_version": 1, + "label": label, + "source_root": str(source_root.resolve()), + "source_sha256": source_hash(source_root), + "environment": environment(), + "cases": cases, + } + with (output / "outputs.json").open("x", encoding="utf-8") as destination: + json.dump(report, destination, indent=2, sort_keys=True, allow_nan=False) + destination.write("\n") + + +def pixels(path: Path) -> tuple[str, list[int]]: + """Hash decoded RGBA pixels, independent of PNG compression.""" + from PIL import Image + + with Image.open(path) as image: + rgba = image.convert("RGBA") + return hashlib.sha256(rgba.tobytes()).hexdigest(), [rgba.height, rgba.width, 4] + + +def read_capture(folder: Path) -> dict[str, object]: + """Validate a manifest and its SVG/PNG artifacts before trusting its hashes.""" + from scripts._vectorization import CASES, file_hash + + report = json.loads((folder / "outputs.json").read_text(encoding="utf-8")) + # Reject non-standard NaN/Infinity literals in edited or external reports. + json.dumps(report, allow_nan=False) + if not isinstance(report, dict) or report.get("schema_version") != 1: + raise ValueError(f"Unsupported capture format: {folder}") + cases = report.get("cases") + if not isinstance(cases, dict) or not cases: + raise ValueError(f"Capture has no cases: {folder}") + required = { + "input", + "colors", + "colors_dtype", + "dimensions", + "bounds", + "svg_sha256", + "rgba_sha256", + "rgba_shape", + } + for name, record in cases.items(): + if ( + name not in CASES + or not isinstance(record, dict) + or not required <= record.keys() + ): + raise ValueError(f"Invalid capture case: {name}") + if file_hash(folder / f"{name}.svg") != record["svg_sha256"]: + raise ValueError(f"SVG does not match its manifest: {folder}/{name}") + digest, shape = pixels(folder / f"{name}.png") + if digest != record["rgba_sha256"] or shape != record["rgba_shape"]: + raise ValueError(f"PNG does not match its manifest: {folder}/{name}") + return report + + +def compare(baseline: Path, candidate: Path) -> int: + """Return one for changed outputs or case sets, and zero for exact equality.""" + before, after = read_capture(baseline), read_capture(candidate) + old, new = before["cases"], after["cases"] + changed = False + for name in sorted(old.keys() | new.keys()): + if name not in old or name not in new: + print(f"{name}: {'added' if name in new else 'missing'} case") + changed = True + elif old[name] != new[name]: + fields = sorted( + key + for key in old[name].keys() | new[name].keys() + if key not in old[name] + or key not in new[name] + or old[name][key] != new[name][key] + ) + print(f"{name}: changed {', '.join(fields)}") + changed = True + if before.get("environment") != after.get("environment"): + print( + "Note: capture environments differ; see outputs.json metadata.", + file=sys.stderr, + ) + if not changed: + print(f"All {len(old)} cases match exactly.") + return int(changed) + + +def main(argv: list[str] | None = None) -> int: + """Capture outputs or compare two saved directories without AWS access.""" + from scripts._vectorization import CASES, ROOT + + parser = argparse.ArgumentParser(description=__doc__) + commands = parser.add_subparsers(dest="command", required=True) + save = commands.add_parser("capture", help="Save SVGs, PNGs and a JSON manifest") + save.add_argument("output", type=Path) + save.add_argument( + "--source-root", + type=Path, + default=ROOT, + help="Trusted checkout to run", + ) + save.add_argument( + "--case", + action="append", + choices=CASES, + help="Repeat to select cases; default: all", + ) + save.add_argument( + "--label", + help="Optional revision or description for the manifest", + ) + diff = commands.add_parser( + "compare", + help="Compare complete captures; exit 1 on changes", + ) + diff.add_argument("baseline", type=Path) + diff.add_argument("candidate", type=Path) + args = parser.parse_args(argv) + try: + if args.command == "compare": + return compare(args.baseline, args.candidate) + capture( + args.output, + list(dict.fromkeys(args.case or CASES)), + args.source_root, + args.label, + ) + return 0 + except (OSError, ValueError, ImportError) as error: + parser.error(str(error)) + + +if __name__ == "__main__": + sys.path.insert(0, str(Path(__file__).resolve().parents[1])) + raise SystemExit(main()) diff --git a/vectorizing/tests/test_developer_tools.py b/vectorizing/tests/test_developer_tools.py new file mode 100644 index 0000000..2df8f3a --- /dev/null +++ b/vectorizing/tests/test_developer_tools.py @@ -0,0 +1,406 @@ +"""Exercise offline reports, failure exits and benchmark measurement contracts.""" + +import copy +import json +import os +from pathlib import Path +from types import SimpleNamespace +from unittest.mock import Mock + +import pytest +from PIL import Image + +from scripts import _vectorization as shared +from scripts import benchmark_vectorization as bench +from scripts import vectorization_outputs as outputs + +SVG = ( + '' + '' +) +DETAILS = { + "input": { + "image": "1px.jpg", + "sha256": "fixture", + "solver": "binary", + "color_count": None, + }, + "colors": [[255, 0, 0, 1]], + "colors_dtype": "int64", + "dimensions": [8, 8], + "bounds": {"left": 0, "top": 0, "right": 8, "bottom": 8, "width": 8, "height": 8}, +} + + +@pytest.fixture +def fake_solver(monkeypatch: pytest.MonkeyPatch) -> None: + """Supply small deterministic outputs without exercising numerical algorithms.""" + monkeypatch.setattr( + shared, + "prepare_case", + lambda *_: lambda: (SVG, copy.deepcopy(DETAILS)), + ) + monkeypatch.setattr(shared, "environment", lambda: {"python": "fixture"}) + + +def save_capture(folder: Path, *names: str) -> dict[str, object]: + """Capture fixture outputs through the public command interface.""" + args = ["capture", str(folder)] + for name in names or ("1px_binary",): + args += ["--case", name] + assert outputs.main(args) == 0 + return json.loads((folder / "outputs.json").read_text()) + + +def test_capture_and_compare(tmp_path: Path, fake_solver: None) -> None: + """Artifacts contain actual SVG/pixel hashes and compare across metadata labels.""" + before, after = tmp_path / "before", tmp_path / "after" + report = save_capture(before) + save_capture(after) + assert (before / "1px_binary.svg").read_bytes() == SVG.encode() + record = report["cases"]["1px_binary"] + assert record["rgba_shape"] == [8, 8, 4] + assert record["rgba_sha256"] == outputs.pixels(before / "1px_binary.png")[0] + assert record["svg_sha256"] == shared.file_hash(before / "1px_binary.svg") + report["label"] = "different label" + report["environment"] = {"python": "other runtime"} + report["source_sha256"] = "different source" + (after / "outputs.json").write_text(json.dumps(report)) + assert outputs.main(["compare", str(before), str(after)]) == 0 + + +@pytest.mark.parametrize( + "field", + ["colors", "colors_dtype", "dimensions", "bounds", "input"], +) +def test_changed_metadata_fails( + tmp_path: Path, + fake_solver: None, + field: str, +) -> None: + """Equal rendered pixels cannot hide changed solver metadata or input identity.""" + before, after = tmp_path / "before", tmp_path / "after" + save_capture(before) + report = save_capture(after) + report["cases"]["1px_binary"][field] = "changed" + (after / "outputs.json").write_text(json.dumps(report)) + assert outputs.main(["compare", str(before), str(after)]) == 1 + + +def test_changed_svg_fails(tmp_path: Path, fake_solver: None) -> None: + """Different SVG bytes fail even when both versions render identically.""" + before, after = tmp_path / "before", tmp_path / "after" + save_capture(before) + report = save_capture(after) + path = after / "1px_binary.svg" + path.write_bytes(path.read_bytes() + b"\n") + report["cases"]["1px_binary"]["svg_sha256"] = shared.file_hash(path) + (after / "outputs.json").write_text(json.dumps(report)) + assert outputs.main(["compare", str(before), str(after)]) == 1 + + +def test_changed_pixels_fail(tmp_path: Path, fake_solver: None) -> None: + """Raster differences fail even when the SVG and solver metadata match.""" + before, after = tmp_path / "before", tmp_path / "after" + save_capture(before) + report = save_capture(after) + Image.new("RGBA", (8, 8), "blue").save(after / "1px_binary.png") + report["cases"]["1px_binary"]["rgba_sha256"] = outputs.pixels( + after / "1px_binary.png", + )[0] + (after / "outputs.json").write_text(json.dumps(report)) + assert outputs.main(["compare", str(before), str(after)]) == 1 + + +def test_changed_case_sets_fail(tmp_path: Path, fake_solver: None) -> None: + """Neither missing nor extra cases are silently skipped.""" + before, after = tmp_path / "before", tmp_path / "after" + save_capture(before) + save_capture(after, "1px_binary", "empty-color") + assert outputs.main(["compare", str(before), str(after)]) == 1 + assert outputs.main(["compare", str(after), str(before)]) == 1 + + +@pytest.mark.parametrize( + "damage", + ["svg", "png", "missing", "empty", "format", "fields", "nan", "name"], +) +def test_invalid_captures_fail( + tmp_path: Path, + fake_solver: None, + damage: str, +) -> None: + """Corrupted, incomplete and unsupported captures cannot report equality.""" + report = save_capture(tmp_path) + if damage == "svg": + (tmp_path / "1px_binary.svg").write_text("changed") + elif damage == "png": + Image.new("RGBA", (8, 8), "blue").save(tmp_path / "1px_binary.png") + elif damage == "missing": + (tmp_path / "1px_binary.png").unlink() + elif damage == "empty": + report["cases"] = {} + elif damage == "format": + report["schema_version"] = 100 + elif damage == "fields": + del report["cases"]["1px_binary"]["bounds"] + elif damage == "nan": + report["cases"]["1px_binary"]["bounds"] = float("nan") + else: + report["cases"] = {"../escape": report["cases"]["1px_binary"]} + (tmp_path / "outputs.json").write_text(json.dumps(report)) + with pytest.raises(SystemExit) as error: + outputs.main(["compare", str(tmp_path), str(tmp_path)]) + assert error.value.code == 2 + + +def test_refuse_overwrites(tmp_path: Path, fake_solver: None) -> None: + """Existing captures and benchmark reports survive accidental repeated commands.""" + save_capture(tmp_path) + original = (tmp_path / "outputs.json").read_bytes() + for command, args in [ + (outputs.main, ["capture", str(tmp_path), "--case", "1px_binary"]), + (bench.main, ["--output", str(tmp_path / "outputs.json")]), + ]: + with pytest.raises(SystemExit) as error: + command(args) + assert error.value.code == 2 + assert (tmp_path / "outputs.json").read_bytes() == original + + +@pytest.mark.parametrize("kind", ["capture", "benchmark"]) +def test_racing_writer_cannot_overwrite( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, + kind: str, +) -> None: + """Files created after the initial existence check are also protected.""" + path = tmp_path / ("1px_binary.svg" if kind == "capture" else "report.json") + + def other_capture(*_: object) -> object: + path.write_text("another writer") + return lambda: (SVG, DETAILS) + + def other_benchmark(*_: object) -> tuple[dict[str, object], bool]: + path.write_text("another writer") + return {}, True + + monkeypatch.setattr(shared, "prepare_case", other_capture) + monkeypatch.setattr(bench, "benchmark", other_benchmark) + with pytest.raises(SystemExit) as error: + if kind == "capture": + outputs.main(["capture", str(tmp_path), "--case", "1px_binary"]) + else: + bench.main(["--output", str(path)]) + assert error.value.code == 2 + assert path.read_text() == "another writer" + + +def test_failed_capture_has_no_manifest( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """A failed run cannot leave a manifest advertising a complete baseline.""" + monkeypatch.setattr(shared, "prepare_case", Mock(side_effect=ValueError("failed"))) + with pytest.raises(SystemExit): + outputs.main(["capture", str(tmp_path), "--case", "1px_binary"]) + assert not (tmp_path / "outputs.json").exists() + + +@pytest.mark.parametrize("platform,value", [("linux", 3072), ("darwin", 3145728)]) +def test_rss_units(monkeypatch: pytest.MonkeyPatch, platform: str, value: int) -> None: + """Linux KiB and macOS byte counters both become MiB.""" + resource = pytest.importorskip("resource") + monkeypatch.setattr(bench.sys, "platform", platform) + monkeypatch.setattr( + resource, + "getrusage", + lambda _: SimpleNamespace(ru_maxrss=value), + ) + assert bench.peak_rss_mib() == 3 + + +def test_alternation_medians_and_equality(monkeypatch: pytest.MonkeyPatch) -> None: + """Paired samples alternate order and report medians rather than best runs.""" + order = [] + times = {"baseline": iter([9, 1, 5]), "candidate": iter([3, 1, 2])} + + def measure(name: str, root: Path, warmups: int) -> dict[str, object]: + order.append(root.name) + assert name == "bubbles" and warmups == 2 + return { + "elapsed_ms": next(times[root.name]), + "peak_rss_mib": 12, + "output": {"same": True}, + "consistent": True, + } + + monkeypatch.setattr(bench, "run_sample", measure) + cases, equal = bench.benchmark( + ["bubbles"], + {name: Path(name) for name in times}, + repeats=3, + warmups=2, + ) + assert order == [ + "baseline", + "candidate", + "candidate", + "baseline", + "baseline", + "candidate", + ] + assert equal + assert cases["bubbles"]["medians"]["baseline"]["elapsed_ms"] == 5 + assert cases["bubbles"]["medians"]["candidate"]["elapsed_ms"] == 2 + + +@pytest.mark.parametrize("inconsistent", [False, True]) +def test_benchmark_mismatches_save_failing_report( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, + inconsistent: bool, +) -> None: + """Cross-version changes and within-process nondeterminism both fail the command.""" + + def measure(name: str, root: Path, warmups: int) -> dict[str, object]: + return { + "elapsed_ms": 1, + "peak_rss_mib": 2, + "consistent": not inconsistent, + "output": {"svg": "same" if inconsistent else str(root)}, + } + + monkeypatch.setattr(bench, "run_sample", measure) + path = tmp_path / "report.json" + assert ( + bench.main( + [ + "--output", + str(path), + "--baseline-root", + str(tmp_path), + "--case", + "bubbles", + "--repeats", + "1", + ], + ) + == 1 + ) + assert json.loads(path.read_text())["outputs_equal"] is False + + +def test_warmups_and_instability( + fake_solver: None, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Warmups execute before measurement and their changed output is not ignored.""" + run = Mock(side_effect=[(SVG, DETAILS), (SVG + "\n", DETAILS), (SVG, DETAILS)]) + monkeypatch.setattr(shared, "prepare_case", lambda *_: run) + monkeypatch.setattr(bench, "peak_rss_mib", lambda: 1.0) + monkeypatch.setattr( + shared, + "environment", + lambda: {"completed_runs": run.call_count}, + ) + row = bench.sample("1px_binary", shared.ROOT, warmups=2) + assert run.call_count == 3 + assert row["environment"]["completed_runs"] == 3 + assert row["consistent"] is False + assert row["elapsed_ms"] >= 0 + + +def test_instability_between_samples_fails(monkeypatch: pytest.MonkeyPatch) -> None: + """Separately stable processes must also agree with one another.""" + rows = [ + { + "elapsed_ms": 1, + "peak_rss_mib": 2, + "consistent": True, + "output": {"svg": value}, + } + for value in ["first", "second"] + ] + monkeypatch.setattr(bench, "run_sample", Mock(side_effect=rows)) + _, equal = bench.benchmark(["bubbles"], {"candidate": shared.ROOT}, 2, 0) + assert not equal + + +def test_worker_failure(monkeypatch: pytest.MonkeyPatch) -> None: + """A failed native worker propagates its error instead of yielding a timing.""" + process = Mock( + return_value=SimpleNamespace(returncode=7, stdout="", stderr="worker crashed"), + ) + monkeypatch.setattr(bench.subprocess, "run", process) + with pytest.raises(RuntimeError, match="worker crashed"): + bench.run_sample("bubbles", shared.ROOT, 1) + command = process.call_args.args[0] + assert command[0] == bench.sys.executable + assert Path(command[1]).is_absolute() + assert process.call_args.kwargs.get("shell", False) is False + + +@pytest.mark.parametrize( + "flag,value", + [("--repeats", "0"), ("--repeats", "-1"), ("--warmups", "-1")], +) +def test_invalid_sample_counts(flag: str, value: str) -> None: + """Invalid counts fail before any solver or worker runs.""" + with pytest.raises(SystemExit) as error: + bench.main([flag, value]) + assert error.value.code == 2 + + +@pytest.mark.skipif( + bench.sys.platform != "darwin" and not bench.sys.platform.startswith("linux"), + reason="Peak RSS measurement requires Linux or macOS", +) +def test_real_workers_are_offline_and_isolated( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Fresh workers resolve fixtures outside the repo cwd without AWS settings.""" + monkeypatch.chdir(tmp_path) + for name in ["PORT", "S3_BUCKET", "AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY"]: + monkeypatch.delenv(name, raising=False) + first = bench.run_sample("1px_binary", shared.ROOT, 0) + second = bench.run_sample("1px_binary", shared.ROOT, 0) + assert first["pid"] != second["pid"] != os.getpid() + assert first["output"] == second["output"] + assert first["peak_rss_mib"] > 0 + assert first["environment"]["versions"]["numpy"] + + +def test_empty_bounds_are_valid_json() -> None: + """An empty color result retains infinite bounds as JSON-safe strings.""" + svg, details = shared.prepare_case("empty-color", shared.ROOT)() + assert details["colors"] == [] + assert details["bounds"]["left"] == "inf" + assert details["bounds"]["width"] == "-inf" + json.dumps(shared.fingerprint(svg, details), allow_nan=False) + + +def test_wrong_import_root_fails( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """An already imported checkout cannot be mistaken for another source root.""" + monkeypatch.setattr(shared.sys, "path", list(shared.sys.path)) + (tmp_path / "vectorizing").mkdir() + (tmp_path / "vectorizing" / "__init__.py").write_text("") + with pytest.raises(ValueError, match="different checkout"): + shared.prepare_case("1px_binary", tmp_path) + + +def test_source_fingerprint(tmp_path: Path) -> None: + """Runtime edits change provenance; test-file edits do not.""" + folder = tmp_path / "vectorizing" + (folder / "tests").mkdir(parents=True) + code = folder / "solver.py" + code.write_text("first") + before = shared.source_hash(tmp_path) + (folder / "tests" / "test_solver.py").write_text("test") + assert shared.source_hash(tmp_path) == before + code.write_text("second") + assert shared.source_hash(tmp_path) != before From 351fa3469e5ee587ed2af5bccbfe24e8afab3ddb Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Fri, 18 Sep 2026 16:54:58 +0200 Subject: [PATCH 09/16] docs: add repository agent guidance (#81) --- AGENTS.md | 104 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 104 insertions(+) create mode 100644 AGENTS.md diff --git a/AGENTS.md b/AGENTS.md new file mode 100644 index 0000000..5b999a6 --- /dev/null +++ b/AGENTS.md @@ -0,0 +1,104 @@ +# Repository guide + +Python 3.11 / Flask service that converts raster images to SVG using NumPy, +OpenCV, FAISS, scikit-image and Potrace. Requests can return raw SVG or upload it +to S3. Start with `README.md` for setup and usage. + +## Code map + +- `vectorizing/__init__.py`: app factory, request validation, cropping and API responses. +- `vectorizing/solvers/binary/`: binary masks and tracing. +- `vectorizing/solvers/color/`: quantization, cluster cleanup, ordered masks and tracing. +- `vectorizing/geometry/` and `vectorizing/svg/`: path conversion, bounds and SVG serialization. +- `vectorizing/util/`: image loading, color-mode normalization and size limits. +- `vectorizing/server/`: environment settings, S3, logging and timing. +- `vectorizing/tests/`: API contracts, image gallery and algorithm regressions. +- `scripts/`: local infrastructure, dependency generation and offline comparison/benchmark tools. + +## Development and checks + +Prefer Docker Compose; it supplies Moto S3 and needs no AWS account or `.env` file. +Run from the repository root: + +```sh +docker compose up --build +pre-commit run --all-files +docker compose --profile testing run --build --rm test +``` + +For a focused test run: + +```sh +docker compose --profile testing run --build --rm test \ + python -m pytest vectorizing/tests/test_color_bitmap_rims.py +``` + +- The API defaults to `http://localhost:8000` in Compose. +- Application source is copied into the image, not bind-mounted. Rebuild after edits. +- Use `docker compose down` to stop services you started; Moto data is discarded. + Isolate project names and image tags when testing alongside other sessions/worktrees. +- Native execution needs the Python dependencies and system libraries from the + Dockerfile/dev-container setup. Package imports require `PORT` and `S3_BUCKET`; + integration tests also require a distinct `S3_TEST_BUCKET` and a local S3 endpoint. +- Preserve normal AWS behavior unless `AWS_ENDPOINT_URL` is explicitly configured. + Use Moto for validation, not live buckets. +- CI runs the pre-commit hooks with Python 3.11 and the Compose test command. + +## Output and behavior contracts + +- Keep smooth anti-aliasing and transparent exteriors. Do not hide seams with SVG + strokes or `shape-rendering="crispEdges"`, or reduce normal tracing quality. +- Color masks use bounded overlaps, not full underpainting. The current rim is + two processed-image pixels; zoom enlarges it and very thin features may remain + covered. Do not promise universally exact holes and seam-free rendering. +- Preserve palette/centroid ordering, dtypes and overflow behavior, connectivity, + and independent mask storage when optimizing arrays. Rim conversion runs forward + because the next mask must still be cumulative. +- Preserve public defaults, response/error shapes, return containers, SVG paint + order and numeric formatting during refactors or performance work. +- Image readers currently wrap all loading failures, including interrupts, and URL + downloads have no timeout. These are tested legacy contracts, not recommendations; + change them deliberately with updated tests, never incidentally during lint cleanup. +- Comments and docstrings should explain behavior and invariants, not edit history. + +## Regression evidence + +- Add focused tests for changed behavior. Keep reference implementations independent + of the optimized code they check. +- The gallery can auto-create missing PNG baselines. A newly seeded baseline does + **not** prove equivalence; do not delete or replace baselines just to make tests pass. +- For output-preserving changes, capture before editing (or use a trusted baseline + checkout), then compare SVG bytes, RGBA pixels, palettes, dimensions and bounds + with `scripts/vectorization_outputs.py`. See the README for commands. +- For layer/geometry changes, check layer deletion, zero alpha and half opacity, + transparent backgrounds and thin features, including `aftermath.png`. An assembled + render alone cannot establish editability. +- Use `scripts/benchmark_vectorization.py` for measured performance claims. Retain + raw samples, check equivalent outputs, and report runtime/hardware context. Its + timing excludes input decoding, HTTP/S3 and rasterization; process peak RSS includes + startup and warmups. Local results are not production or concurrent-load guarantees. + +## Style, dependencies and artifacts + +- Follow `.pre-commit-config.yaml` and `pyproject.toml`: Black, 88 columns, isort, + annotations and NumPy-style docstrings. Avoid broad lint suppressions and keep + correctness/security checks enabled. Passing lint is not a static-type-check claim. +- Prefer existing dependencies. Edit `requirements/prod.in` or `requirements/dev.in`, + then use `scripts/compile_requirements.sh` and `scripts/compile_envs.sh` when dependency + updates are needed. The latter requires the configured Conda `dev` environment. + Keep system dependency setup consistent with `scripts/install_system_dependencies.sh` + and the Dockerfile. +- Keep generated captures, benchmarks, investigations and scratch source under `.user/` + or temporary directories, not tracked code. `.user/` is excluded from Git and Docker. + Historical notes there may be stale; verify them against current source. +- Keep visual evidence local unless upload is explicitly requested. Never include + credentials in reports or commits. + +## Pull requests + +Keep descriptions short and plain-language. Fetch `.github/pull_request_template.md` +from the `Kittl/.github` repository rather than inventing a replacement. +Leave owner attestations unchecked without explicit approval. Do not add agent/tool +badges. After addressing human review feedback, reply but leave the thread open +unless the user explicitly asks to resolve it; uncertain reviewer identity counts +as human. From 8287c3b3bd91711c52ae06367323b92c5090d8c4 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Mon, 21 Sep 2026 11:43:07 +0200 Subject: [PATCH 10/16] fix(api): return raw SVG with correct MIME type (#83) --- vectorizing/__init__.py | 2 +- vectorizing/tests/test_api_contracts.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/vectorizing/__init__.py b/vectorizing/__init__.py index 1abf422..26d04e5 100644 --- a/vectorizing/__init__.py +++ b/vectorizing/__init__.py @@ -130,7 +130,7 @@ def index() -> str | Response | tuple[Response, int]: timer.end_timer() if raw: - return markup + return Response(markup, mimetype="image/svg+xml") timer.start_timer("Markup Upload") cuid_str = upload_markup(markup, S3_BUCKET) diff --git a/vectorizing/tests/test_api_contracts.py b/vectorizing/tests/test_api_contracts.py index 4c050c3..c46236a 100644 --- a/vectorizing/tests/test_api_contracts.py +++ b/vectorizing/tests/test_api_contracts.py @@ -84,6 +84,7 @@ def test_raw_requests_crop_before_vectorizing_and_do_not_upload( }, ) assert response.status_code == 200 + assert response.mimetype == "image/svg+xml" assert response.data.startswith(b" Date: Tue, 22 Sep 2026 16:33:37 +0200 Subject: [PATCH 11/16] perf(color): make cluster cleanup linear and memory-bounded (#74) * perf(color): make cluster cleanup linear and memory-bounded * test(color): split regression suites and document invariants * perf(color): reuse the invariant interior mask * docs: shorten the test setup notes * perf(color): bound component labeling to each color region Release unused boundary masks and crop labeling, counts and writes to each color's bounding box. Keep neighbor influence global so cropping preserves cleanup decisions and editable holes. Add sparse-region regressions covering disconnected islands, borders, unused colors and transposed inputs. Bounding-box overhead can outweigh savings for colors spanning nearly the full image. --- README.md | 3 + docker-compose.yml | 2 +- pytest.ini | 2 +- vectorizing/solvers/color/quantize.py | 123 +++---- vectorizing/tests/color_reference.py | 105 ++++++ vectorizing/tests/test.py | 349 -------------------- vectorizing/tests/test_color_bitmaps.py | 85 +++++ vectorizing/tests/test_color_centroids.py | 59 ++++ vectorizing/tests/test_color_cleanup.py | 224 +++++++++++++ vectorizing/tests/test_color_equivalence.py | 83 +++++ vectorizing/tests/test_integration.py | 133 ++++++++ 11 files changed, 733 insertions(+), 435 deletions(-) create mode 100644 vectorizing/tests/color_reference.py delete mode 100644 vectorizing/tests/test.py create mode 100644 vectorizing/tests/test_color_bitmaps.py create mode 100644 vectorizing/tests/test_color_centroids.py create mode 100644 vectorizing/tests/test_color_cleanup.py create mode 100644 vectorizing/tests/test_color_equivalence.py create mode 100644 vectorizing/tests/test_integration.py diff --git a/README.md b/README.md index b2e2bc0..2d534bb 100644 --- a/README.md +++ b/README.md @@ -144,6 +144,9 @@ To run tests against the local Moto service, run: docker compose --profile testing run --build --rm test ``` +Tests are split into `test_*.py` files in `vectorizing/tests`. Compose and CI +run them all. `color_reference.py` keeps the old code for before/after checks. + When running pytest outside Compose, configure the AWS variables for an S3-compatible service first. ### Required setup diff --git a/docker-compose.yml b/docker-compose.yml index 9389ea5..c0a2cee 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -57,4 +57,4 @@ services: depends_on: moto-init: condition: service_completed_successfully - command: python -m pytest vectorizing/tests + command: python -m pytest diff --git a/pytest.ini b/pytest.ini index 7a166d7..ab009e8 100644 --- a/pytest.ini +++ b/pytest.ini @@ -1,3 +1,3 @@ [pytest] pythonpath = . -python_files = test.py test_*.py *_test.py \ No newline at end of file +testpaths = vectorizing/tests diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index 5963217..109210a 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -20,12 +20,6 @@ def bilateral_filter( return cv2.bilateralFilter(img_arr, d, s, s) -def dilate(matrix: np.ndarray) -> np.ndarray: - """Dilate labels with a two-by-two kernel and OpenCV's default anchor.""" - kernel = np.ones((2, 2)) - return cv2.dilate(matrix, kernel) - - def fill_holes(matrix: np.ndarray) -> np.ndarray: """Replace zero cells with their nearest nonzero value via a distance transform.""" closest = ndi.distance_transform_edt( @@ -42,89 +36,50 @@ def enhance( labels: np.ndarray, colors: np.ndarray, ) -> tuple[np.ndarray, np.ndarray]: - """Remove components mostly covered by neighboring colors, then fill holes.""" - dims = img_arr.shape[:2] - - # 0 will be reserved for "unwritten" cells, or holes + """Remove boundary-dominated components with O(K*N) work and O(N) image storage.""" + # Reserve zero for holes, preserving the existing input-dtype shift behavior. labels = labels + 1 - - clusters = [ - # Even though we don't allow it, technically the max - # value in labels (before adding 1) is 255, so it's safer - # to convert to uint16 to avoid overflows - np.where(labels == idx + 1, idx + 1, 0).astype(np.uint16) - for idx, _ in enumerate(colors) - ] - - # For each cluster, store a matrix of its connected components - # skimage's default connectivity includes diagonal neighbors. - original_connected_components_list = [label(cluster) + 1 for cluster in clusters] - - # Bincounts for each connected components matrix - # Meaning bincount[i] = num_appearances(matrix, i) - # It's used later to determine what should be erased - connected_components_bincounts = [ - np.bincount(connected_components.flatten()) - for connected_components in original_connected_components_list - ] - - # Make a copy of the connected components - # These will be modified and compared with the originals later - connected_components_list = [ - np.array(item, copy=True) for item in original_connected_components_list - ] - - for x, cluster_x in enumerate(clusters): - dilated_cluster_x = dilate(cluster_x) - - for y, cluster_y in enumerate(clusters): - if x == y: - continue - - # The overlap between dilated_cluster_x and cluster_y, - # meaning, the part of cluster_y that dilated_cluster_x covers - overlap = np.logical_and(dilated_cluster_x, cluster_y) - - # Remove overlap from connected components - connected_components_list[y] = np.where( - overlap, - 0, - connected_components_list[y], - ) - - for x, connected_components in enumerate(connected_components_list): - original_bincount = connected_components_bincounts[x] - count = original_bincount.shape[0] - - new_bincount = np.bincount( - connected_components.flatten(), - minlength=count, # Force same length + valid = (labels > 0) & (labels <= len(colors)) + + # OpenCV's 2x2 dilation (default anchor/border) reaches a pixel from above, + # left, and upper-left. Mark overlap from any OTHER palette color once, + # without treating missing/out-of-palette neighbors as a dilated cluster. + boundary = np.zeros(labels.shape, dtype=bool) + boundary[1:, :] |= valid[:-1, :] & (labels[1:, :] != labels[:-1, :]) + boundary[:, 1:] |= valid[:, :-1] & (labels[:, 1:] != labels[:, :-1]) + boundary[1:, 1:] |= valid[:-1, :-1] & (labels[1:, 1:] != labels[:-1, :-1]) + + # The boundary is fixed; reuse its complement for every color's area count. + interior = ~boundary + del boundary, valid + cleaned = np.zeros(img_arr.shape[:2], dtype=np.uint16 if len(colors) else np.uint8) + # One scan finds every color's box, including all disconnected components. + # max_label excludes invalid labels; zero would instead infer the maximum. + regions = ndi.find_objects(labels, max_label=len(colors)) if len(colors) else [] + for index, region in enumerate(regions): + if region is None: + continue + cluster = labels[region] == index + 1 + # Keep full (8-neighbor) connectivity, including diagonal contacts. + components = label(cluster, connectivity=2) + original_counts = np.bincount(components.ravel()) + interior_counts = np.bincount( + # Slice the global mask: other colors outside the box still influence it. + components[interior[region]], + minlength=len(original_counts), ) - areas_ratio = np.divide( - new_bincount.astype(np.float32), - original_bincount.astype(np.float32), - out=np.ones((count,), dtype=np.float32), - where=original_bincount != 0, - ) - - # Update cluster - # Connected components that lost more than 0.9 of their original area - # are completely removed, others are kept - clusters[x] = np.where( - areas_ratio[original_connected_components_list[x]] <= 0.1, - 0, - clusters[x], + interior_counts.astype(np.float32), + original_counts.astype(np.float32), + out=np.ones(len(original_counts), dtype=np.float32), + where=original_counts != 0, ) + # Retain whole components, using the same float32, inclusive <=0.1 cutoff. + cleaned[region][cluster & (areas_ratio[components] > 0.1)] = index + 1 + # Release this map before allocating the next color's component map. + del components - # Update labels with new cluster data - labels = np.zeros(dims).astype(np.uint8) - for cluster in clusters: - labels = np.where(labels == 0, cluster, labels) - - # Fill holes - labels = fill_holes(labels) - return labels - 1, colors + return fill_holes(cleaned) - 1, colors # Try to get the cluster of pixels that represent a transparent background diff --git a/vectorizing/tests/color_reference.py b/vectorizing/tests/color_reference.py new file mode 100644 index 0000000..c67b9e8 --- /dev/null +++ b/vectorizing/tests/color_reference.py @@ -0,0 +1,105 @@ +"""Frozen pre-optimization algorithms used as independent regression oracles. + +Keep these intentionally slow implementations separate from production helpers: +sharing optimized code would let a regression affect both sides of a comparison. +Cleanup shares only the unchanged fill_holes step so tests can bypass it in both +paths to inspect component removal before nearest-neighbor filling hides holes. +""" + +import cv2 +import numpy as np +from PIL import Image +from skimage.measure import label + +from vectorizing.solvers.color import quantize as color_quantize + + +def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: + """Preserve the RGB-pixel centroid algorithm from before PR 71.""" + img = ( + Image.fromarray(img_arr) + .quantize(color_count, method=Image.Quantize.FASTOCTREE) + .convert("RGB") + ) + pixels = np.asarray(img) + return np.unique(pixels.reshape(-1, pixels.shape[-1]), axis=0).astype(np.uint8) + + +def legacy_create_bitmaps( + labels: np.ndarray, + colors: np.ndarray, + has_background: bool, +) -> tuple[list[np.ndarray], list[np.ndarray]]: + """Preserve the pairwise bitmap accumulation from before PR 73.""" + bitmaps = [ + np.where(labels == index, 1, 0).astype(np.uint32) + for index in range(len(colors)) + ] + if has_background: + bitmaps = bitmaps[1:] + colors = colors[1:] + zipped = list(zip(bitmaps, colors)) + zipped = [[bitmap, color] for bitmap, color in zipped if np.sum(bitmap) > 0] + bitmaps = [bitmap for bitmap, _ in zipped] + colors = [color for _, color in zipped] + for x in range(len(bitmaps)): + bitmap_x = bitmaps[x] + for y in range(x + 1, len(bitmaps)): + bitmap_x += bitmaps[y] + bitmaps[x] = bitmap_x + return bitmaps, colors + + +def legacy_enhance( + img_arr: np.ndarray, + labels: np.ndarray, + colors: np.ndarray, +) -> tuple[np.ndarray, np.ndarray]: + """Preserve the pairwise cleanup from main at f69c69b, before PR 74.""" + dims = img_arr.shape[:2] + labels = labels + 1 + clusters = [ + np.where(labels == idx + 1, idx + 1, 0).astype(np.uint16) + for idx, _ in enumerate(colors) + ] + # Preserve integer labeling, full connectivity and shifted component IDs. + # The optimized path must match this, not redefine the expected behavior. + original_connected_components_list = [label(cluster) + 1 for cluster in clusters] + connected_components_bincounts = [ + np.bincount(connected_components.flatten()) + for connected_components in original_connected_components_list + ] + connected_components_list = [ + np.array(item, copy=True) for item in original_connected_components_list + ] + # Keep the expensive pairwise dilation scans: independence is the point. + for x, cluster_x in enumerate(clusters): + dilated_cluster_x = cv2.dilate(cluster_x, np.ones((2, 2))) + for y, cluster_y in enumerate(clusters): + if x == y: + continue + overlap = np.logical_and(dilated_cluster_x, cluster_y) + connected_components_list[y] = np.where( + overlap, + 0, + connected_components_list[y], + ) + for x, connected_components in enumerate(connected_components_list): + original_bincount = connected_components_bincounts[x] + count = original_bincount.shape[0] + new_bincount = np.bincount(connected_components.flatten(), minlength=count) + areas_ratio = np.divide( + new_bincount.astype(np.float32), + original_bincount.astype(np.float32), + out=np.ones((count,), dtype=np.float32), + where=original_bincount != 0, + ) + clusters[x] = np.where( + areas_ratio[original_connected_components_list[x]] <= 0.1, + 0, + clusters[x], + ) + labels = np.zeros(dims).astype(np.uint8) + for cluster in clusters: + labels = np.where(labels == 0, cluster, labels) + return color_quantize.fill_holes(labels) - 1, colors diff --git a/vectorizing/tests/test.py b/vectorizing/tests/test.py deleted file mode 100644 index edd5e40..0000000 --- a/vectorizing/tests/test.py +++ /dev/null @@ -1,349 +0,0 @@ -"""Check image rendering, storage and exact color-optimization equivalence.""" - -import os -from io import BytesIO -from pathlib import Path -from unittest.mock import Mock - -import numpy as np -import pytest -from cairosvg import svg2png -from flask.testing import FlaskClient -from PIL import Image - -from vectorizing.geometry.bounds import compound_paths_bounds -from vectorizing.server.s3 import get_s3_client -from vectorizing.server.timer import Timer -from vectorizing.solvers.color import quantize as color_quantize -from vectorizing.solvers.color.bitmaps import create_bitmaps -from vectorizing.solvers.color.ColorSolver import ColorSolver -from vectorizing.svg.markup import generate_SVG_markup -from vectorizing.tests import testutil -from vectorizing.tests.config import TESTS -from vectorizing.tests.testutil import ( - MAX_IMAGE_DIFFERENCE, - RESULTS_FOLDER_PATH, - compute_img_difference, - get_image_url, - get_markup, - write_img_difference, -) - - -def test(client: FlaskClient) -> None: - """Render the configured gallery and compare or seed its local PNG baselines.""" - results_path = Path(RESULTS_FOLDER_PATH) - - # Create results folder if non-existent - if not results_path.exists(): - results_path.mkdir() - - # Cache test results to allow all tests to run - diffs = [] - - for img_name, options_list in TESTS.items(): - for options in options_list: - id = options.get("id") - output_name = f"{id}.png" - - # Vectorized SVG markup - markup = get_markup(client, img_name, options) - - # Rasterized SVG - png = svg2png(bytestring=markup) - img = Image.open(BytesIO(png)).convert("RGB") - - # Store result if it doesn't exist yet - results_output_path = Path(RESULTS_FOLDER_PATH / output_name) - if not results_output_path.exists(): - img.save(results_output_path) - - else: - # Difference between result and expected result - difference = compute_img_difference( - img, - RESULTS_FOLDER_PATH / output_name, - ) - - # Write image difference to diff_output - if difference >= MAX_IMAGE_DIFFERENCE: - write_img_difference( - img, - RESULTS_FOLDER_PATH / output_name, - output_name, - ) - - diffs.append(difference) - - assert all([diff <= MAX_IMAGE_DIFFERENCE for diff in diffs]) - - -def test_write_img_difference_handles_rgba_baselines( - tmp_path: Path, - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Normalize transparent baseline pixels before computing RGB differences.""" - baseline = tmp_path / "baseline.png" - output = tmp_path / "difference.png" - Image.new("RGBA", (2, 2), (0, 0, 0, 0)).save(baseline) - monkeypatch.setattr(testutil, "DIFF_OUTPUT_FOLDER_PATH", tmp_path) - - testutil.write_img_difference( - Image.new("RGB", (2, 2), (255, 255, 255)), - baseline, - output.name, - ) - - assert output.exists() - - -def test_color_solver_preserves_empty_transparent_image() -> None: - """Keep every rendered pixel transparent for an empty input image.""" - image = Image.open(Path(__file__).parent / "images" / "empty.png") - paths, colors, width, height = ColorSolver(image, 6, Timer()).solve() - markup = generate_SVG_markup(paths, colors, width, height) - rendered = Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA") - - assert rendered.getchannel("A").getextrema() == (0, 0) - - -def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: - """Freeze the original RGB-pixel algorithm as an independent regression oracle.""" - img = ( - Image.fromarray(img_arr) - .quantize(color_count, method=Image.Quantize.FASTOCTREE) - .convert("RGB") - ) - pixels = np.asarray(img) - return np.unique(pixels.reshape(-1, pixels.shape[-1]), axis=0).astype(np.uint8) - - -@pytest.mark.parametrize( - "variant", - ["noise", "strided", "one-pixel", "solid", "sparse"], -) -@pytest.mark.parametrize("color_count", [2, 6, 16, 64]) -@pytest.mark.parametrize("seed", range(5)) -def test_initial_centroids_match_original( - color_count: int, - seed: int, - variant: str, -) -> None: - """Preserve exact dtype, values and ordering on random and sparse RGB inputs.""" - rng = np.random.default_rng(seed) - noise = rng.integers(0, 256, size=(63, 67, 3), dtype=np.uint8) - pixels = { - "noise": noise, - "strided": noise[::2, ::2], - "one-pixel": noise[:1, :1], - "solid": np.full_like(noise, (175, 80, 230)), # Ignore unused black entries. - "sparse": (noise // 128) * 128, - }[variant] - expected = legacy_initial_centroids(pixels, color_count) - actual = color_quantize.get_initial_centroids(pixels, color_count) - np.testing.assert_equal(actual.dtype, expected.dtype) - np.testing.assert_equal(actual.dtype, np.dtype(np.uint8)) - np.testing.assert_array_equal(actual, expected) - - -def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Keep only used RGB colors, deduplicated and sorted rather than palette order.""" - indexed = Image.new("P", (3, 1)) - indexed.putdata([7, 3, 5]) - palette = np.zeros((256, 3), dtype=np.uint8) - palette[1] = (255, 0, 0) # Unused nonblack entry. - palette[3] = palette[7] = (90, 10, 20) # Duplicate used RGB entries. - palette[5] = (10, 20, 30) - indexed.putpalette(palette.ravel().tolist()) - with monkeypatch.context() as patch: - patch.setattr(Image.Image, "quantize", lambda *args, **kwargs: indexed) - pixels = np.zeros((1, 3, 3), dtype=np.uint8) - actual = color_quantize.get_initial_centroids(pixels, 64) - expected = legacy_initial_centroids(pixels, 64) - np.testing.assert_array_equal(actual, expected) - np.testing.assert_array_equal(actual, [[10, 20, 30], [90, 10, 20]]) - - -def legacy_create_bitmaps( - labels: np.ndarray, - colors: np.ndarray, - has_background: bool, -) -> tuple[list[np.ndarray], list[np.ndarray]]: - """Freeze the original pairwise accumulation as an independent regression oracle.""" - bitmaps = [ - np.where(labels == index, 1, 0).astype(np.uint32) - for index in range(len(colors)) - ] - if has_background: - bitmaps = bitmaps[1:] - colors = colors[1:] - zipped = list(zip(bitmaps, colors)) - zipped = [[bitmap, color] for bitmap, color in zipped if np.sum(bitmap) > 0] - bitmaps = [bitmap for bitmap, _ in zipped] - colors = [color for _, color in zipped] - for x in range(len(bitmaps)): - bitmap_x = bitmaps[x] - for y in range(x + 1, len(bitmaps)): - bitmap_x += bitmaps[y] - bitmaps[x] = bitmap_x - return bitmaps, colors - - -@pytest.mark.parametrize( - "variant", - ["noise", "strided", "one-row", "one-column", "solid", "background", "sparse"], -) -@pytest.mark.parametrize("color_count", [1, 2, 6, 16, 64, 65]) -@pytest.mark.parametrize("has_background", [False, True]) -@pytest.mark.parametrize("seed", range(3)) -def test_bitmap_layering_matches_original( - color_count: int, - has_background: bool, - seed: int, - variant: str, -) -> None: - """Preserve masks, dtype, color order and read-only inputs across label patterns.""" - rng = np.random.default_rng(seed) - noise = rng.integers(0, color_count, size=(19, 23), dtype=np.uint16) - colors = rng.integers(0, 256, size=(color_count, 4), dtype=np.uint8) - colors.setflags(write=False) - labels = { - "noise": noise, - "strided": noise[::2, ::2], - "one-row": noise[:1, :], - "one-column": noise[:, :1], - "solid": np.full_like(noise, color_count - 1), - "background": np.zeros_like(noise), - "sparse": noise % 2, - }[variant] - labels.setflags(write=False) - expected_bitmaps, expected_colors = legacy_create_bitmaps( - labels, - colors, - has_background, - ) - actual_bitmaps, actual_colors = create_bitmaps(labels, colors, has_background) - np.testing.assert_array_equal(actual_colors, expected_colors) - np.testing.assert_equal(len(actual_bitmaps), len(expected_bitmaps)) - for actual, expected in zip(actual_bitmaps, expected_bitmaps): - np.testing.assert_equal(actual.dtype, np.dtype(np.uint32)) - np.testing.assert_array_equal(actual, expected) - - -@pytest.mark.parametrize("has_background", [False, True]) -@pytest.mark.parametrize("color_count", [0, 1, 6]) -def test_bitmap_layering_handles_empty_inputs( - has_background: bool, - color_count: int, -) -> None: - """Return no layers for empty labels or an empty palette.""" - colors = np.zeros((color_count, 3), dtype=np.uint8) - labels = np.empty((0, 3), dtype=np.uint8) - np.testing.assert_equal(create_bitmaps(labels, colors, has_background), ([], [])) - np.testing.assert_equal( - create_bitmaps(np.zeros((2, 2), dtype=np.uint8), colors[:0], has_background), - ([], []), - ) - - -def test_bitmap_layering_preserves_overlap_and_transparency() -> None: - """Keep suffix unions in palette order without including transparent pixels.""" - labels = np.array([[0, 1, 3, 4]], dtype=np.uint8) - colors = np.arange(20, dtype=np.uint8).reshape(5, 4) - # Label zero is transparent; label two is unused between visible layers. - bitmaps, visible_colors = create_bitmaps(labels, colors, True) - expected = np.array( - [[[0, 1, 1, 1]], [[0, 0, 1, 1]], [[0, 0, 0, 1]]], - dtype=np.uint32, - ) - np.testing.assert_array_equal(bitmaps, expected) - np.testing.assert_array_equal(visible_colors, colors[[1, 3, 4]]) - # The in-place accumulation must not make different layers share storage. - bitmaps[0][0, 0] = 1 - np.testing.assert_array_equal(bitmaps[1:], expected[1:]) - np.testing.assert_array_equal(labels, [[0, 1, 3, 4]]) - - -@pytest.mark.parametrize("optimization", ["centroids", "bitmaps"]) -@pytest.mark.parametrize( - "image_name, color_count", - [ - ("bubbles.png", 5), - ("shapes_2.png", 7), - ("aftermath.png", 2), - ("aftermath.png", 6), - ("aftermath.png", 16), - ("aftermath.png", 64), - ("empty.png", 6), - ("1px.jpg", 9), - ], -) -def test_color_optimizations_preserve_vectorization( - image_name: str, - color_count: int, - optimization: str, - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Compare final SVG, colors, dimensions and bounds against the old algorithm.""" - with Image.open(Path(__file__).parent / "images" / image_name) as image: - actual = ColorSolver(image, color_count, Timer()).solve() - target, legacy = { - "centroids": ( - "vectorizing.solvers.color.quantize.get_initial_centroids", - legacy_initial_centroids, - ), - "bitmaps": ( - "vectorizing.solvers.color.ColorSolver.create_bitmaps", - legacy_create_bitmaps, - ), - }[optimization] - # Patch each lookup site and verify the legacy implementation was used. - reference = Mock(wraps=legacy) - monkeypatch.setattr(target, reference) - expected = ColorSolver(image, color_count, Timer()).solve() - reference.assert_called_once() - - actual_paths, actual_colors, actual_width, actual_height = actual - expected_paths, expected_colors, expected_width, expected_height = expected - np.testing.assert_array_equal(actual_colors, expected_colors) - np.testing.assert_equal( - (actual_width, actual_height), - (expected_width, expected_height), - ) - np.testing.assert_equal( - compound_paths_bounds(actual_paths), - compound_paths_bounds(expected_paths), - ) - # Byte-identical SVG is stricter than a raster tolerance and includes transparency. - np.testing.assert_equal( - generate_SVG_markup(*actual), - generate_SVG_markup(*expected), - ) - - -def test_uploads_markup_to_s3(client: FlaskClient) -> None: - """Store the generated SVG with its media type and return the object's key.""" - response = client.post( - "/", - json={ - "url": get_image_url("black_rectangle.png"), - "solver": 0, - "raw": False, - }, - ) - - assert response.status_code == 200 - payload = response.get_json() - test_bucket = os.environ["S3_TEST_BUCKET"] - s3 = get_s3_client() - try: - stored = s3.get_object( - Bucket=test_bucket, - Key=payload["objectId"], - ) - assert stored["ContentType"] == "image/svg+xml" - assert stored["Body"].read().startswith(b" None: + """Preserve masks, dtype, color order and read-only inputs across label patterns.""" + rng = np.random.default_rng(seed) + noise = rng.integers(0, color_count, size=(19, 23), dtype=np.uint16) + colors = rng.integers(0, 256, size=(color_count, 4), dtype=np.uint8) + colors.setflags(write=False) + labels = { + "noise": noise, + "strided": noise[::2, ::2], + "one-row": noise[:1, :], + "one-column": noise[:, :1], + "solid": np.full_like(noise, color_count - 1), + "background": np.zeros_like(noise), + "sparse": noise % 2, + }[variant] + labels.setflags(write=False) + expected_bitmaps, expected_colors = legacy_create_bitmaps( + labels, + colors, + has_background, + ) + actual_bitmaps, actual_colors = create_bitmaps(labels, colors, has_background) + np.testing.assert_array_equal(actual_colors, expected_colors) + np.testing.assert_equal(len(actual_bitmaps), len(expected_bitmaps)) + for actual, expected in zip(actual_bitmaps, expected_bitmaps): + np.testing.assert_equal(actual.dtype, np.dtype(np.uint32)) + np.testing.assert_array_equal(actual, expected) + + +@pytest.mark.parametrize("has_background", [False, True]) +@pytest.mark.parametrize("color_count", [0, 1, 6]) +def test_bitmap_layering_handles_empty_inputs( + has_background: bool, + color_count: int, +) -> None: + """Return no layers for empty labels or an empty palette.""" + colors = np.zeros((color_count, 3), dtype=np.uint8) + labels = np.empty((0, 3), dtype=np.uint8) + np.testing.assert_equal(create_bitmaps(labels, colors, has_background), ([], [])) + np.testing.assert_equal( + create_bitmaps(np.zeros((2, 2), dtype=np.uint8), colors[:0], has_background), + ([], []), + ) + + +def test_bitmap_layering_preserves_overlap_and_transparency() -> None: + """Keep suffix unions in palette order without including transparent pixels.""" + labels = np.array([[0, 1, 3, 4]], dtype=np.uint8) + colors = np.arange(20, dtype=np.uint8).reshape(5, 4) + # Label zero is transparent; label two is unused between visible layers. + bitmaps, visible_colors = create_bitmaps(labels, colors, True) + expected = np.array( + [[[0, 1, 1, 1]], [[0, 0, 1, 1]], [[0, 0, 0, 1]]], + dtype=np.uint32, + ) + np.testing.assert_array_equal(bitmaps, expected) + np.testing.assert_array_equal(visible_colors, colors[[1, 3, 4]]) + # The in-place accumulation must not make different layers share storage. + bitmaps[0][0, 0] = 1 + np.testing.assert_array_equal(bitmaps[1:], expected[1:]) + np.testing.assert_array_equal(labels, [[0, 1, 3, 4]]) diff --git a/vectorizing/tests/test_color_centroids.py b/vectorizing/tests/test_color_centroids.py new file mode 100644 index 0000000..faa63b9 --- /dev/null +++ b/vectorizing/tests/test_color_centroids.py @@ -0,0 +1,59 @@ +"""Used-palette centroid regressions: exact values, dtype and ordering. + +Centroid ordering changes K-means results, so set equality is not sufficient. +""" + +import numpy as np +import pytest +from PIL import Image + +from vectorizing.solvers.color import quantize as color_quantize +from vectorizing.tests.color_reference import legacy_initial_centroids + + +@pytest.mark.parametrize( + "variant", + ["noise", "strided", "one-pixel", "solid", "sparse"], +) +@pytest.mark.parametrize("color_count", [2, 6, 16, 64]) +@pytest.mark.parametrize("seed", range(5)) +def test_initial_centroids_match_original( + color_count: int, + seed: int, + variant: str, +) -> None: + """Preserve exact dtype, values and ordering on random and sparse RGB inputs.""" + rng = np.random.default_rng(seed) + noise = rng.integers(0, 256, size=(63, 67, 3), dtype=np.uint8) + pixels = { + "noise": noise, + "strided": noise[::2, ::2], + "one-pixel": noise[:1, :1], + "solid": np.full_like(noise, (175, 80, 230)), # Ignore unused black entries. + "sparse": (noise // 128) * 128, + }[variant] + expected = legacy_initial_centroids(pixels, color_count) + actual = color_quantize.get_initial_centroids(pixels, color_count) + np.testing.assert_equal(actual.dtype, expected.dtype) + np.testing.assert_equal(actual.dtype, np.dtype(np.uint8)) + np.testing.assert_array_equal(actual, expected) + + +def test_initial_centroids_ignore_unused_and_duplicate_palette_entries( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep only used RGB colors, deduplicated and sorted rather than palette order.""" + indexed = Image.new("P", (3, 1)) + indexed.putdata([7, 3, 5]) + palette = np.zeros((256, 3), dtype=np.uint8) + palette[1] = (255, 0, 0) # Unused nonblack entry. + palette[3] = palette[7] = (90, 10, 20) # Duplicate used RGB entries. + palette[5] = (10, 20, 30) + indexed.putpalette(palette.ravel().tolist()) + with monkeypatch.context() as patch: + patch.setattr(Image.Image, "quantize", lambda *args, **kwargs: indexed) + pixels = np.zeros((1, 3, 3), dtype=np.uint8) + actual = color_quantize.get_initial_centroids(pixels, 64) + expected = legacy_initial_centroids(pixels, 64) + np.testing.assert_array_equal(actual, expected) + np.testing.assert_array_equal(actual, [[10, 20, 30], [90, 10, 20]]) diff --git a/vectorizing/tests/test_color_cleanup.py b/vectorizing/tests/test_color_cleanup.py new file mode 100644 index 0000000..adc6576 --- /dev/null +++ b/vectorizing/tests/test_color_cleanup.py @@ -0,0 +1,224 @@ +"""Cluster cleanup parity, morphology edge cases and component-map lifetime. + +Unfilled comparisons expose the actual keep/remove decisions: hole filling can +otherwise repaint a wrongly removed component and hide the regression. +""" + +import weakref + +import numpy as np +import pytest + +from vectorizing.solvers.color import quantize as color_quantize +from vectorizing.tests.color_reference import legacy_enhance + +# After the final label shift, an unfilled zero wraps to uint16's maximum. +# This sentinel is used only by tests bypassing fill_holes with a nonempty palette. +UNFILLED_LABEL = np.iinfo(np.uint16).max + + +@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) +@pytest.mark.parametrize( + "variant", + [ + "noise", + "strided", + "one-pixel", + "one-row", + "one-column", + "solid", + "sparse", + "checkerboard", + ], +) +# Transparent artwork can add a background entry to the 64 requested colors. +@pytest.mark.parametrize("color_count", [1, 2, 6, 16, 64, 65]) +@pytest.mark.parametrize("seed", range(3)) +def test_cluster_cleanup_matches_original( + before_fill: bool, + variant: str, + color_count: int, + seed: int, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Preserve component decisions and filled labels without mutating inputs.""" + rng = np.random.default_rng(seed) + noise = rng.integers(0, color_count, (19, 23), dtype=np.uint8) + labels = { + "noise": noise, + "strided": noise[::2, ::2], + "one-pixel": noise[:1, :1], + "one-row": noise[:1, :], + "one-column": noise[:, :1], + "solid": np.full_like(noise, color_count - 1), + "sparse": noise % 2, + "checkerboard": ( + np.indices(noise.shape).sum(axis=0) % min(color_count, 2) + ).astype(np.uint8), + }[variant] + colors = rng.integers(0, 256, (color_count, 4), dtype=np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + labels.setflags(write=False) + colors.setflags(write=False) + pixels.setflags(write=False) + original_labels = labels.copy() + if before_fill: + # Compare removal decisions, not just the colors painted over their holes. + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + expected, expected_colors = legacy_enhance(pixels, labels, colors) + actual, actual_colors = color_quantize.enhance(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + np.testing.assert_equal(actual.dtype, expected.dtype) + np.testing.assert_array_equal(actual_colors, expected_colors) + np.testing.assert_equal(actual_colors is colors, True) + np.testing.assert_array_equal(labels, original_labels) + + +@pytest.mark.parametrize("area", [9, 10, 11]) +def test_cluster_cleanup_preserves_inclusive_area_threshold( + area: int, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep a component with 1/9 interior area, but remove 1/10 and 1/11.""" + labels = np.zeros((8, 16), dtype=np.uint8) + # A 2x2 core has one interior pixel at (3, 3). Extending only its top row + # changes the component's total area without adding any interior pixels. + labels[2, 2:area] = 1 + labels[3, 2:4] = 1 + colors = np.zeros((2, 3), dtype=np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + expected = labels.astype(np.uint16) + if area >= 10: + expected[labels == 1] = UNFILLED_LABEL + for cleaner in (legacy_enhance, color_quantize.enhance): + actual, _ = cleaner(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + + +def test_cluster_cleanup_preserves_diagonal_connectivity( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Treat a 2x2 core and its diagonal thin tail as one removable component.""" + labels = np.zeros((8, 16), dtype=np.uint8) + # Seven tail pixels touch the 4-pixel core only at a corner. With full + # connectivity the combined 11-pixel component has 1/11 interior area; + # with 4-neighbor connectivity the core would incorrectly survive at 1/4. + labels[2:4, 2:4] = 1 + labels[4, 4:11] = 1 + colors = np.zeros((2, 3), dtype=np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + expected = labels.astype(np.uint16) + expected[labels == 1] = UNFILLED_LABEL + for cleaner in (legacy_enhance, color_quantize.enhance): + actual, _ = cleaner(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + + +def test_cluster_cleanup_preserves_dilation_anchor_and_border( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """The 2x2 default anchor spares only the isolated top-left corner pixel.""" + labels = np.zeros((5, 5), dtype=np.uint8) + labels[::4, ::4] = 1 + colors = np.zeros((2, 3), dtype=np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + expected = labels.astype(np.uint16) + expected[labels == 1] = UNFILLED_LABEL + # No upper/left source exists at (0, 0); outside the image is not a color. + expected[0, 0] = 1 + for cleaner in (legacy_enhance, color_quantize.enhance): + actual, _ = cleaner(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + + +@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) +@pytest.mark.parametrize("color_count", [0, 1, 3, 256]) +@pytest.mark.parametrize("dtype", [np.uint8, np.uint16, np.int16]) +def test_cluster_cleanup_preserves_unassigned_labels_and_dtype( + color_count: int, + dtype: type[np.generic], + before_fill: bool, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Ignore unassigned neighbors and retain existing label-shift overflow behavior.""" + rng = np.random.default_rng(42) + # 255 + 1 wraps only for uint8; do not silently fix that old behavior here. + # Small palettes also leave labels whose pixels must not dilate into others. + labels = rng.choice([0, 1, 2, 3, 254, 255], size=(7, 9)).astype(dtype) + if dtype == np.int16: + labels[1, 1:3] = [-1, -2] + if before_fill: + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + colors = np.zeros((color_count, 3), dtype=np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + expected, _ = legacy_enhance(pixels, labels, colors) + actual, actual_colors = color_quantize.enhance(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + np.testing.assert_equal(actual.dtype, expected.dtype) + np.testing.assert_equal(actual_colors is colors, True) + + +@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) +@pytest.mark.parametrize("transpose", [False, True]) +def test_cluster_cleanup_crops_labeling_without_losing_neighbor_influence( + before_fill: bool, + transpose: bool, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Crop sparse colors while preserving disjoint islands and outside influences.""" + labels = np.zeros((13, 17), dtype=np.uint8) + labels[2:4, 3:5] = 1 + labels[8, 11] = 1 # A disconnected pixel of the same color must be removed. + labels[0, 14:17] = 2 # A single-row crop touching the image border. + labels[9, 2] = labels[10, 3] = 3 # Diagonal contact within a tight crop. + if transpose: + labels = labels.T + colors = np.zeros((6, 3), dtype=np.uint8) # Two palette entries are unused. + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + if before_fill: + monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) + expected, _ = legacy_enhance(pixels, labels, colors) + original_label = color_quantize.label + shapes = [] + + def record_label(cluster: np.ndarray, connectivity: int) -> np.ndarray: + shapes.append(cluster.shape) + return original_label(cluster, connectivity=connectivity) + + monkeypatch.setattr(color_quantize, "label", record_label) + actual, _ = color_quantize.enhance(pixels, labels, colors) + np.testing.assert_array_equal(actual, expected) + # The background spans the image; each other color gets one minimal box, + # including all of its disconnected pieces, and unused entries get no pass. + expected_shapes = [(13, 17), (7, 9), (1, 3), (2, 2)] + if transpose: + expected_shapes = [(width, height) for height, width in expected_shapes] + np.testing.assert_array_equal(shapes, expected_shapes) + + +def test_cluster_cleanup_releases_each_component_map( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Release the old map before labeling the next color, not only on return.""" + original_label = color_quantize.label + maps: list[weakref.ReferenceType[np.ndarray]] = [] + + def record_label(cluster: np.ndarray, connectivity: int) -> np.ndarray: + # Weak references observe lifetime without keeping the maps alive. + # Checking before allocation catches even a temporary two-map overlap. + np.testing.assert_equal(all(ref() is None for ref in maps), True) + components = original_label(cluster, connectivity=connectivity) + maps.append(weakref.ref(components)) + return components + + monkeypatch.setattr(color_quantize, "label", record_label) + labels = (np.indices((8, 9)).sum(axis=0) % 4).astype(np.uint8) + pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + colors = np.zeros((4, 3), dtype=np.uint8) + color_quantize.enhance(pixels, labels, colors) + # All colors are present: a skipped labeler must not make this pass vacuously. + np.testing.assert_equal(len(maps), 4) + np.testing.assert_equal(all(ref() is None for ref in maps), True) diff --git a/vectorizing/tests/test_color_equivalence.py b/vectorizing/tests/test_color_equivalence.py new file mode 100644 index 0000000..2be8255 --- /dev/null +++ b/vectorizing/tests/test_color_equivalence.py @@ -0,0 +1,83 @@ +"""Full solver regressions comparing exact SVG bytes, colors and geometry. + +Replace one optimization at a time with its frozen reference while retaining the +others. This catches interactions that isolated mask/centroid/cleanup tests miss. +""" + +from pathlib import Path +from unittest.mock import Mock + +import numpy as np +import pytest +from PIL import Image + +from vectorizing.geometry.bounds import compound_paths_bounds +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.tests.color_reference import ( + legacy_create_bitmaps, + legacy_enhance, + legacy_initial_centroids, +) + + +@pytest.mark.parametrize("optimization", ["centroids", "bitmaps", "cleanup"]) +@pytest.mark.parametrize( + "image_name, color_count", + [ + ("bubbles.png", 5), + ("shapes_2.png", 7), + ("aftermath.png", 2), + ("aftermath.png", 6), + ("aftermath.png", 16), + ("aftermath.png", 64), + ("empty.png", 6), + ("1px.jpg", 9), + ], +) +def test_color_optimizations_preserve_vectorization( + image_name: str, + color_count: int, + optimization: str, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Compare final SVG, colors, dimensions and bounds against the old algorithm.""" + with Image.open(Path(__file__).parent / "images" / image_name) as image: + actual = ColorSolver(image, color_count, Timer()).solve() + target, legacy = { + "centroids": ( + "vectorizing.solvers.color.quantize.get_initial_centroids", + legacy_initial_centroids, + ), + "bitmaps": ( + "vectorizing.solvers.color.ColorSolver.create_bitmaps", + legacy_create_bitmaps, + ), + "cleanup": ( + "vectorizing.solvers.color.quantize.enhance", + legacy_enhance, + ), + }[optimization] + # Patch each lookup site and verify the legacy implementation was used. + reference = Mock(wraps=legacy) + monkeypatch.setattr(target, reference) + expected = ColorSolver(image, color_count, Timer()).solve() + reference.assert_called_once() + + actual_paths, actual_colors, actual_width, actual_height = actual + expected_paths, expected_colors, expected_width, expected_height = expected + np.testing.assert_array_equal(actual_colors, expected_colors) + np.testing.assert_equal( + (actual_width, actual_height), + (expected_width, expected_height), + ) + np.testing.assert_equal( + compound_paths_bounds(actual_paths), + compound_paths_bounds(expected_paths), + ) + # Byte-identical SVG is stricter than a raster tolerance and includes transparency. + np.testing.assert_equal( + generate_SVG_markup(*actual), + generate_SVG_markup(*expected), + ) diff --git a/vectorizing/tests/test_integration.py b/vectorizing/tests/test_integration.py new file mode 100644 index 0000000..8cb8231 --- /dev/null +++ b/vectorizing/tests/test_integration.py @@ -0,0 +1,133 @@ +"""HTTP/S3 integration, raster diagnostics and transparent SVG checks. + +The persisted raster gallery is a tolerant smoke test and creates missing +baselines. Exact before/after output checks live in test_color_equivalence.py. +Layer editability and anti-aliased edges are covered by the color layer suites. +""" + +import os +from io import BytesIO +from pathlib import Path + +import pytest +from cairosvg import svg2png +from flask.testing import FlaskClient +from PIL import Image + +from vectorizing.server.s3 import get_s3_client +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.tests import testutil +from vectorizing.tests.config import TESTS +from vectorizing.tests.testutil import ( + MAX_IMAGE_DIFFERENCE, + RESULTS_FOLDER_PATH, + compute_img_difference, + get_image_url, + get_markup, + write_img_difference, +) + + +def test(client: FlaskClient) -> None: + """Render the configured gallery and compare or seed its local PNG baselines.""" + results_path = Path(RESULTS_FOLDER_PATH) + + # Create results folder if non-existent + if not results_path.exists(): + results_path.mkdir() + + # Cache test results to allow all tests to run + diffs = [] + + for img_name, options_list in TESTS.items(): + for options in options_list: + id = options.get("id") + output_name = f"{id}.png" + + # Vectorized SVG markup + markup = get_markup(client, img_name, options) + + # Rasterized SVG + png = svg2png(bytestring=markup) + img = Image.open(BytesIO(png)).convert("RGB") + + # Store result if it doesn't exist yet + results_output_path = Path(RESULTS_FOLDER_PATH / output_name) + if not results_output_path.exists(): + img.save(results_output_path) + + else: + # Difference between result and expected result + difference = compute_img_difference( + img, + RESULTS_FOLDER_PATH / output_name, + ) + + # Write image difference to diff_output + if difference >= MAX_IMAGE_DIFFERENCE: + write_img_difference( + img, + RESULTS_FOLDER_PATH / output_name, + output_name, + ) + + diffs.append(difference) + + assert all([diff <= MAX_IMAGE_DIFFERENCE for diff in diffs]) + + +def test_write_img_difference_handles_rgba_baselines( + tmp_path: Path, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Normalize transparent baseline pixels before computing RGB differences.""" + baseline = tmp_path / "baseline.png" + output = tmp_path / "difference.png" + Image.new("RGBA", (2, 2), (0, 0, 0, 0)).save(baseline) + monkeypatch.setattr(testutil, "DIFF_OUTPUT_FOLDER_PATH", tmp_path) + + testutil.write_img_difference( + Image.new("RGB", (2, 2), (255, 255, 255)), + baseline, + output.name, + ) + + assert output.exists() + + +def test_color_solver_preserves_empty_transparent_image() -> None: + """Keep every rendered pixel transparent for an empty input image.""" + image = Image.open(Path(__file__).parent / "images" / "empty.png") + paths, colors, width, height = ColorSolver(image, 6, Timer()).solve() + markup = generate_SVG_markup(paths, colors, width, height) + rendered = Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA") + + assert rendered.getchannel("A").getextrema() == (0, 0) + + +def test_uploads_markup_to_s3(client: FlaskClient) -> None: + """Store the generated SVG with its media type and return the object's key.""" + response = client.post( + "/", + json={ + "url": get_image_url("black_rectangle.png"), + "solver": 0, + "raw": False, + }, + ) + + assert response.status_code == 200 + payload = response.get_json() + test_bucket = os.environ["S3_TEST_BUCKET"] + s3 = get_s3_client() + try: + stored = s3.get_object( + Bucket=test_bucket, + Key=payload["objectId"], + ) + assert stored["ContentType"] == "image/svg+xml" + assert stored["Body"].read().startswith(b" Date: Fri, 25 Sep 2026 12:40:54 +0200 Subject: [PATCH 12/16] feat: preserve color detail with compact SVG output (#85) * feat: preserve color detail with compact SVG output * fix: preserve quadratic paths and recover failed canvas clips Handle unassigned distance labels on long images and retain strict validated ARM64/x86 geometry checks with an exact mask checksum. --- README.md | 27 +- vectorizing/solvers/color/ColorSolver.py | 57 +++- vectorizing/solvers/color/quantize.py | 200 ++++++----- vectorizing/svg/markup.py | 168 ++++++--- vectorizing/tests/color_reference.py | 93 ++--- vectorizing/tests/test_color_cleanup.py | 319 ++++++------------ vectorizing/tests/test_color_equivalence.py | 14 +- vectorizing/tests/test_color_layer_artwork.py | 25 +- vectorizing/tests/test_color_p3.py | 252 ++++++++++++++ vectorizing/tests/test_integration.py | 9 +- vectorizing/tests/test_svg_geometry.py | 196 +++++++++++ vectorizing/tests/test_svg_markup.py | 17 +- 12 files changed, 916 insertions(+), 461 deletions(-) create mode 100644 vectorizing/tests/test_color_p3.py create mode 100644 vectorizing/tests/test_svg_geometry.py diff --git a/README.md b/README.md index 2d534bb..3b500ad 100644 --- a/README.md +++ b/README.md @@ -123,6 +123,29 @@ A typical response would be Or, if `raw = true` was supplied, just plain SVG markup +Color processing uses a gentle 3-pixel bilateral filter and removes only connected +components smaller than eight processed-image pixels, rather than rejecting thin +regions based on their shape. Transparent pixels are protected; on opaque images, +the most common surviving perimeter color is also protected to retain small +background-colored letter counters. This can retain extra small specks of that +color. Tracing retains small paths and uses a curve optimization tolerance of 0.5. +The existing 1,048,576-pixel area cap, default of six +colors and supported range of 2–64 colors are unchanged. Color paths touching the +canvas are extended before tracing and clipped back to the image so corners remain +covered and returned bounds do not include the padding. If Skia rejects a canvas +clip, that layer is retraced without padding and a warning is logged. Recovery +constrains any outlying curve control points to the canvas. It keeps smooth editable +vectors instead of failing the request, but can adjust curves near the canvas and +round corners inward, reducing edge coverage on the affected layer. + +SVGs use compact absolute/relative commands on an integer hundredth-pixel grid, +inside a `scale(.01)` group. This preserves the previous two-decimal coordinate +rounding, viewport, paint order and opacity without raster images or SVG strokes. +Binary tracing is unchanged, but both solvers use the compact serializer. Equivalent +geometry can produce small renderer-specific antialiasing differences; exact pixel +identity across viewers and zoom levels is not guaranteed. Potrace and pypotrace +remain dependencies under their existing GPL licenses. + Color layers have cutouts with a small overlap along shared edges to hide seams. The overlap is two pixels in the resized image before tracing, not screen pixels. Hiding a color can expose this rim; very thin features may remain covered, and @@ -145,7 +168,9 @@ docker compose --profile testing run --build --rm test ``` Tests are split into `test_*.py` files in `vectorizing/tests`. Compose and CI -run them all. `color_reference.py` keeps the old code for before/after checks. +run them all. `color_reference.py` keeps independent centroid, bitmap and area-cleanup +oracles. The color acceptance tests also check the approved Aftermath geometry, +Bubble Whirl's lettering counters, alpha behavior and compact SVG coordinates. When running pytest outside Compose, configure the AWS variables for an S3-compatible service first. diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index 545c833..a4382af 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -1,8 +1,10 @@ """Trace editable color layers with bounded overlap at shared edges.""" +import logging + import numpy as np import potrace -from pathops import Path +from pathops import Path, PathOp, PathOpsError, op from PIL import Image from vectorizing.geometry.potrace import potrace_path_to_compound_path @@ -12,6 +14,53 @@ from vectorizing.util.limit_size import limit_size +def _trace_mask(bitmap: np.ndarray) -> Path: + """Trace a mask with the same detail settings on normal and recovery paths.""" + traced = potrace.Bitmap(bitmap).trace(turdsize=0, opttolerance=0.5, alphamax=1) + return potrace_path_to_compound_path(traced) + + +def trace_bitmap(bitmap: np.ndarray) -> Path: + """Trace detail without speck removal, extending then clipping canvas edges.""" + height, width = bitmap.shape + # Potrace rounds exposed mask corners. Extending edge labels moves that + # rounding outside the viewport instead of leaving transparent canvas corners. + mask = bitmap.astype(np.uint8) + padded = np.pad(mask, 2, mode="edge") + path = _trace_mask(padded).transform(1, 0, 0, 1, -2, -2) + left, top, right, bottom = path.bounds + if left < 0 or top < 0 or right > width or bottom > height: + # Keep returned geometry/bounds inside the image, not just the SVG's + # viewport. This also makes layer exports safe without the original clip. + canvas = Path() + canvas.moveTo(0, 0) + canvas.lineTo(width, 0) + canvas.lineTo(width, height) + canvas.lineTo(0, height) + canvas.close() + try: + path = op(path, canvas, PathOp.INTERSECTION) + except PathOpsError: + # Recovery keeps smooth, bounded vectors and does not repeat the + # failing boolean operation. Unpadded tracing can round canvas + # corners inward; only this exceptional layer loses edge coverage. + logging.getLogger(__name__).warning( + "Canvas clipping failed; retracing without padding", + exc_info=True, + ) + traced = _trace_mask(mask) + path = Path(fillType=traced.fillType) + pen = path.getPen() + # Even unpadded fitted curves can overshoot the canvas. Constrain + # their control hull on recovery, without another boolean operation. + for command, points in traced.segments: + bounded = tuple( + (min(width, max(0, x)), min(height, max(0, y))) for x, y in points + ) + getattr(pen, command)(*bounded) + return path + + class ColorSolver: """Resize and quantize an image, then trace its ordered color layers.""" @@ -40,13 +89,9 @@ def solve(self) -> list[list[Path] | list[np.ndarray] | int]: self.timer.end_timer() self.timer.start_timer("Bitmap Tracing") - traced_bitmaps = [potrace.Bitmap(bitmap).trace() for bitmap in bitmaps] + compound_paths = [trace_bitmap(bitmap) for bitmap in bitmaps] self.timer.end_timer() - compound_paths = [ - potrace_path_to_compound_path(traced) for traced in traced_bitmaps - ] - return [compound_paths, colors, self.img.size[0], self.img.size[1]] diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index 109210a..d38c1fb 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -1,92 +1,91 @@ -"""Quantize RGB colors while keeping transparent background pixels separate.""" +"""Quantize colors without discarding connected thin features or alpha holes.""" import cv2 import numpy as np -import scipy.ndimage as ndi from faiss import Kmeans from PIL import Image +from scipy.ndimage import distance_transform_edt from skimage.measure import label -BILATERAL_FILTER_DIAMETER = 7 -BILATERAL_FILTER_SIGMA = 50 +MIN_COMPONENT_AREA = 8 -def bilateral_filter( - img_arr: np.ndarray, - d: int = BILATERAL_FILTER_DIAMETER, - s: float = BILATERAL_FILTER_SIGMA, -) -> np.ndarray: - """Smooth clip-art colors while preserving edges; photos may lose detail.""" - return cv2.bilateralFilter(img_arr, d, s, s) +def bilateral_filter(img_arr: np.ndarray) -> np.ndarray: + """Gently smooth local color noise without the broad blur of a large kernel.""" + return cv2.bilateralFilter(img_arr, 3, 12, 1) -def fill_holes(matrix: np.ndarray) -> np.ndarray: - """Replace zero cells with their nearest nonzero value via a distance transform.""" - closest = ndi.distance_transform_edt( - np.logical_not(matrix), - return_distances=False, - return_indices=True, - ) - matrix = np.where(matrix != 0, matrix, matrix[closest[0], closest[1]]) - return matrix +def _perimeter(array: np.ndarray) -> np.ndarray: + """Read each boundary pixel once, including single-row or single-column images.""" + if min(array.shape) == 1: + return array.ravel() + return np.concatenate([array[0], array[-1], array[1:-1, 0], array[1:-1, -1]]) -def enhance( - img_arr: np.ndarray, +def clean_components( labels: np.ndarray, - colors: np.ndarray, -) -> tuple[np.ndarray, np.ndarray]: - """Remove boundary-dominated components with O(K*N) work and O(N) image storage.""" - # Reserve zero for holes, preserving the existing input-dtype shift behavior. - labels = labels + 1 - valid = (labels > 0) & (labels <= len(colors)) - - # OpenCV's 2x2 dilation (default anchor/border) reaches a pixel from above, - # left, and upper-left. Mark overlap from any OTHER palette color once, - # without treating missing/out-of-palette neighbors as a dilated cluster. - boundary = np.zeros(labels.shape, dtype=bool) - boundary[1:, :] |= valid[:-1, :] & (labels[1:, :] != labels[:-1, :]) - boundary[:, 1:] |= valid[:, :-1] & (labels[:, 1:] != labels[:, :-1]) - boundary[1:, 1:] |= valid[:-1, :-1] & (labels[1:, 1:] != labels[:-1, :-1]) - - # The boundary is fixed; reuse its complement for every color's area count. - interior = ~boundary - del boundary, valid - cleaned = np.zeros(img_arr.shape[:2], dtype=np.uint16 if len(colors) else np.uint8) - # One scan finds every color's box, including all disconnected components. - # max_label excludes invalid labels; zero would instead infer the maximum. - regions = ndi.find_objects(labels, max_label=len(colors)) if len(colors) else [] - for index, region in enumerate(regions): - if region is None: - continue - cluster = labels[region] == index + 1 - # Keep full (8-neighbor) connectivity, including diagonal contacts. - components = label(cluster, connectivity=2) - original_counts = np.bincount(components.ravel()) - interior_counts = np.bincount( - # Slice the global mask: other colors outside the box still influence it. - components[interior[region]], - minlength=len(original_counts), - ) - areas_ratio = np.divide( - interior_counts.astype(np.float32), - original_counts.astype(np.float32), - out=np.ones(len(original_counts), dtype=np.float32), - where=original_counts != 0, + background: np.ndarray | None, +) -> np.ndarray: + """Refill tiny components, protecting transparency and background-color counters. + + Area, not the proportion of interior pixels, determines removal, retaining + thin components above the cutoff. Connectivity includes diagonal contacts. + The labeled chamfer transform assigns removed pixels to surviving neighbors; + when nothing survives, retain the input instead of inventing a replacement. + For opaque images, protect the most common surviving perimeter color so small + enclosed letter counters are not filled. Ties use the lowest palette index. + + Parameters + ---------- + labels : numpy.ndarray + Two-dimensional palette indices, including zero for any background. + background : numpy.ndarray or None + Nonzero at protected transparent pixels, if present. + + Returns + ------- + numpy.ndarray + Cleaned labels with the input dtype; the input is never mutated. + """ + components = label(labels.astype(np.uint16) + 1, background=0, connectivity=2) + counts = np.bincount(components.ravel()) + holes = counts[components] < MIN_COMPONENT_AREA + if background is not None: + holes &= background == 0 + elif holes.any() and not holes.all(): + perimeter = _perimeter(labels)[~_perimeter(holes)] + if perimeter.size: + background_color = np.bincount(perimeter).argmax() + holes &= labels != background_color + if not holes.any() or holes.all(): + return labels + + _, nearest = cv2.distanceTransformWithLabels( + holes.astype(np.uint8), + cv2.DIST_L2, + 5, + labelType=cv2.DIST_LABEL_PIXEL, + ) + lookup = np.zeros(int(nearest.max()) + 1, dtype=labels.dtype) + lookup[nearest[~holes]] = labels[~holes] + cleaned = labels.copy() + cleaned[holes] = lookup[nearest[holes]] + unassigned = holes & (nearest == 0) + if unassigned.any(): + # OpenCV can leave zero labels beyond its distance propagation limit + # on very wide/tall images. Zero is not a seed: use an exact fallback + # only there, preserving normal chamfer assignments and tie breaking. + indices = distance_transform_edt( + holes, + return_distances=False, + return_indices=True, ) - # Retain whole components, using the same float32, inclusive <=0.1 cutoff. - cleaned[region][cluster & (areas_ratio[components] > 0.1)] = index + 1 - # Release this map before allocating the next color's component map. - del components - - return fill_holes(cleaned) - 1, colors + cleaned[unassigned] = labels[tuple(indices[:, unassigned])] + return cleaned -# Try to get the cluster of pixels that represent a transparent background -# If there is no transparent background, return None -# This is needed because RGBA quantization is very volatile, and sometimes -# opaque colors get assigned to the same clusters as highly transparent ones. -# So we focus on the solid image + transparent background case for now. +# Keep transparent pixels separate from RGB clustering: otherwise opaque and +# transparent pixels with similar RGB values can be assigned to the same color. def get_background_cluster(img_arr: np.ndarray, t: float = 0.5) -> np.ndarray | None: """Return an alpha mask if any raw alpha is below t, otherwise return None.""" r, g, b, a = cv2.split(img_arr) @@ -99,8 +98,6 @@ def get_background_cluster(img_arr: np.ndarray, t: float = 0.5) -> np.ndarray | return None -# Write the background cluster on top of a matrix of clusters (labels) -# The background cluster has priority def write_background_cluster(labels: np.ndarray, bg_cluster: np.ndarray) -> np.ndarray: """Shift labels by one, reserving zero for the overriding background mask.""" labels = labels + 1 @@ -111,13 +108,9 @@ def write_background_cluster(labels: np.ndarray, bg_cluster: np.ndarray) -> np.n def get_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: """Return sorted unique used RGB palette colors for K-means initialization.""" img = Image.fromarray(img_arr) - img = img.quantize(color_count, method=Image.Quantize.FASTOCTREE) - - # Ignore unused entries: palette padding must not add extra K-means clusters. - # Keep np.unique's RGB order and deduplication, but sort only the used palette - # rather than every pixel. Centroid order affects K-means results. - # quantize() returns mode P: at most 256 entries, within getcolors()'s cap. + # Palette padding must not introduce additional clusters. RGB order affects + # initialization, so sort the used entries rather than the entire pixel grid. used_indices = [index for _, index in img.getcolors()] palette = np.asarray(img.getpalette("RGB"), dtype=np.uint8).reshape(-1, 3) return np.unique(palette[used_indices], axis=0) @@ -141,28 +134,25 @@ def quantize( img_arr: np.ndarray, color_count: int, ) -> tuple[np.ndarray, np.ndarray, bool]: - """Return cleaned labels, palette colors and whether a background was isolated.""" - channel_count = img_arr.shape[-1] - - background_cluster = None - if channel_count == 4: - background_cluster = get_background_cluster(img_arr) - img = Image.fromarray(img_arr) - img = img.convert("RGB") - img_arr = np.asarray(img) - - img_arr = bilateral_filter(img_arr) - - labels, colors = kmeans(img_arr, get_initial_centroids(img_arr, color_count)) - - labels = np.reshape(labels, img_arr.shape[:-1]) - - has_background = background_cluster is not None - if has_background: - labels = write_background_cluster(labels, background_cluster) - colors = [[0, 0, 0, 0]] + [[r, g, b, 1] for r, g, b in colors] - colors = np.array(colors) - - colors = colors.astype(np.uint8) - labels, colors = enhance(img_arr, labels, colors) - return labels, colors, has_background + """Return area-cleaned labels, an RGB-ordered palette and background status.""" + background = get_background_cluster(img_arr) if img_arr.shape[-1] == 4 else None + rgb = bilateral_filter(img_arr[:, :, :3].copy()) + labels, colors = kmeans(rgb, get_initial_centroids(rgb, color_count)) + labels = labels.reshape(rgb.shape[:2]) + + # Paint order determines which neighboring colors may receive a bounded rim. + order = np.lexsort(colors.T[::-1]) + labels = np.argsort(order)[labels].astype(np.uint16) + colors = colors[order] + if background is not None: + labels = write_background_cluster(labels, background) + colors = np.vstack( + [ + np.zeros((1, 4), dtype=np.uint8), + np.column_stack([colors, np.ones(len(colors), dtype=np.uint8)]), + ], + ) + labels = clean_components(labels, background) + if background is not None: + labels = np.where(background > 0, 0, labels) + return labels, colors, background is not None diff --git a/vectorizing/svg/markup.py b/vectorizing/svg/markup.py index 643e7b6..9dfb8a9 100644 --- a/vectorizing/svg/markup.py +++ b/vectorizing/svg/markup.py @@ -1,9 +1,12 @@ -"""Serialize traced paths without strokes or changes to their paint order.""" +"""Serialize editable filled paths on an exact hundredth-pixel coordinate grid.""" from collections.abc import Iterable, Sequence import numpy as np -from pathops import Path +from pathops import Path, PathVerb + +Point = tuple[int, int] +Command = tuple[str, tuple[int, ...]] def truncate(number: float) -> str: @@ -14,13 +17,99 @@ def truncate(number: float) -> str: def to_SVG_color_string(color: Sequence[float] | np.ndarray) -> str: """Format RGB or RGBA components without scaling or rounding their values.""" func = "rgb" if len(color) == 3 else "rgba" - tuple = "".join( - [ - f"{item}," if i != len(color) - 1 else f"{item}" - for i, item in enumerate(color) - ], - ) - return f"{func}({tuple})" + return f"{func}({','.join(str(item) for item in color)})" + + +def _color_string(color: Sequence[float] | np.ndarray) -> str: + """Use short hex for opaque integral RGB, preserving other color/alpha values.""" + opaque = len(color) == 3 or color[3] == 1 + integral = all(0 <= value <= 255 and value == int(value) for value in color[:3]) + if opaque and integral: + rgb = "".join(f"{int(value):02x}" for value in color[:3]) + return "#" + (rgb[::2] if rgb[::2] == rgb[1::2] else rgb) + return to_SVG_color_string(color) + + +def _point(point: tuple[float, float]) -> Point: + """Keep decimal-format rounding, including half ties, before changing units.""" + # Multiplying a float by 100 and rounding can disagree with formatting it + # first (e.g. 2.675). No additional precision is lost by the integer encoding. + return tuple(int(truncate(value).replace(".", "")) for value in point) + + +def _variants( + command: str, + points: tuple[Point, ...], + current: Point, + control: Point | None, +) -> list[Command]: + """Offer equivalent absolute, relative, axial and reflected cubic commands.""" + absolute = tuple(value for point in points for value in point) + relative = tuple(value - current[i % 2] for i, value in enumerate(absolute)) + variants = [(command, absolute), (command.lower(), relative)] + if command == "L": + if points[0][1] == current[1]: + variants.extend([("H", (absolute[0],)), ("h", (relative[0],))]) + if points[0][0] == current[0]: + variants.extend([("V", (absolute[1],)), ("v", (relative[1],))]) + if command == "C" and control is not None: + reflected = (2 * current[0] - control[0], 2 * current[1] - control[1]) + if points[0] == reflected: + variants.extend([("S", absolute[2:]), ("s", relative[2:])]) + return variants + + +def _shortest(variants: list[Command], previous: str) -> tuple[str, str]: + """Choose the shortest legal spelling, eliding repeated commands when allowed.""" + candidates = [] + for command, values in variants: + numbers = " ".join(str(value) for value in values).replace(" -", "-") + candidates.append((command + numbers, command)) + # Extra moveto pairs are lines, not new subpaths: never omit an M/m. + implicit_line = (previous, command) in [("M", "L"), ("m", "l")] + if command.upper() != "M" and (previous == command or implicit_line): + separator = "" if numbers.startswith("-") else " " + candidates.append((separator + numbers, command)) + return min(candidates, key=lambda candidate: len(candidate[0])) + + +def _path_data(path: Path, width: int, height: int) -> str: + """Encode filled geometry without changing contour order or winding.""" + pieces = [] + current = start = (0, 0) + control = None + previous = "" + # The segment-pen interface coalesces adjacent quadratics with implied + # endpoints. Raw verbs expose each control/end pair required by SVG Q/q. + for kind, coordinates in path: + if kind == PathVerb.CLOSE: + pieces.append("z") + current = start + control = None + previous = "z" + continue + # Canvas clipping can reduce a cubic to a quadratic; retain those too. + command = { + PathVerb.MOVE: "M", + PathVerb.LINE: "L", + PathVerb.CUBIC: "C", + PathVerb.QUAD: "Q", + }[kind] + points = tuple(_point(point) for point in coordinates) + variants = _variants(command, points, current, control) + x, y = points[-1] + if x in (0, width * 100) or y in (0, height * 100): + # Some renderers accumulate subpixel error in relative commands. + # Anchor canvas boundaries explicitly (not H/V, which retain one + # current coordinate) to keep opaque edge pixels fully covered. + variants = variants[:1] + text, previous = _shortest(variants, previous) + pieces.append(text) + current = points[-1] + if command == "M": + start = current + control = points[1] if command == "C" else None + return "".join(pieces) def generate_SVG_markup( @@ -29,41 +118,36 @@ def generate_SVG_markup( width: int, height: int, ) -> str: - """Serialize line/cubic paths in paint order, skipping empty geometry.""" - paths_markup = [] + """Emit compact vectors with unchanged viewport, paint order and alpha values. - for compound_path, color in zip(compound_paths, colors): - segments = list(compound_path.segments) - if not len(segments): - continue + Integer coordinates with a 0.01 scale represent the same two-decimal geometry + as absolute pixel coordinates. Relative commands and transforms can still + cause small renderer-specific antialiasing differences; this is not a promise + of pixel-identical rendering at every zoom level. - d = "" - for segment in segments: - command = segment[0] - if command == "moveTo": - x = segment[1][0][0] - y = segment[1][0][1] - d += f"M {truncate(x)} {truncate(y)} " - if command == "lineTo": - x = segment[1][0][0] - y = segment[1][0][1] - d += f"L {truncate(x)} {truncate(y)} " - if command == "curveTo": - d += ( - "C" + f"{truncate(segment[1][0][0])},{truncate(segment[1][0][1])} " - f"{truncate(segment[1][1][0])},{truncate(segment[1][1][1])} " - f"{truncate(segment[1][2][0])},{truncate(segment[1][2][1])} " - ) - if command == "closePath": - d += "Z" - - path_markup = f'' - paths_markup.append(path_markup) - - paths_markup = "\n".join(paths_markup) + Parameters + ---------- + compound_paths : Iterable[Path] + Line/quadratic/cubic compound paths in paint order. + colors : Iterable[Sequence[float] | numpy.ndarray] + Corresponding RGB or RGBA colors; alpha is not rescaled. + width : int + Viewport width in pixels. + height : int + Viewport height in pixels. + + Returns + ------- + str + SVG markup with real filled paths and no strokes. + """ + paths_markup = [] + for path, color in zip(compound_paths, colors): + data = _path_data(path, width, height) + if data: + paths_markup.append(f'') return ( f'\n' - f"\n{paths_markup}\n\n" - f"" + f'viewBox="0 0 {width} {height}">' + '' + "".join(paths_markup) + "" ) diff --git a/vectorizing/tests/color_reference.py b/vectorizing/tests/color_reference.py index c67b9e8..2b93675 100644 --- a/vectorizing/tests/color_reference.py +++ b/vectorizing/tests/color_reference.py @@ -1,17 +1,10 @@ -"""Frozen pre-optimization algorithms used as independent regression oracles. +"""Independent, intentionally slow oracles for optimized color operations.""" -Keep these intentionally slow implementations separate from production helpers: -sharing optimized code would let a regression affect both sides of a comparison. -Cleanup shares only the unchanged fill_holes step so tests can bypass it in both -paths to inspect component removal before nearest-neighbor filling hides holes. -""" +from collections import Counter import cv2 import numpy as np from PIL import Image -from skimage.measure import label - -from vectorizing.solvers.color import quantize as color_quantize def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: @@ -50,56 +43,36 @@ def legacy_create_bitmaps( return bitmaps, colors -def legacy_enhance( - img_arr: np.ndarray, +def reference_clean_components( labels: np.ndarray, - colors: np.ndarray, -) -> tuple[np.ndarray, np.ndarray]: - """Preserve the pairwise cleanup from main at f69c69b, before PR 74.""" - dims = img_arr.shape[:2] - labels = labels + 1 - clusters = [ - np.where(labels == idx + 1, idx + 1, 0).astype(np.uint16) - for idx, _ in enumerate(colors) - ] - # Preserve integer labeling, full connectivity and shifted component IDs. - # The optimized path must match this, not redefine the expected behavior. - original_connected_components_list = [label(cluster) + 1 for cluster in clusters] - connected_components_bincounts = [ - np.bincount(connected_components.flatten()) - for connected_components in original_connected_components_list - ] - connected_components_list = [ - np.array(item, copy=True) for item in original_connected_components_list - ] - # Keep the expensive pairwise dilation scans: independence is the point. - for x, cluster_x in enumerate(clusters): - dilated_cluster_x = cv2.dilate(cluster_x, np.ones((2, 2))) - for y, cluster_y in enumerate(clusters): - if x == y: - continue - overlap = np.logical_and(dilated_cluster_x, cluster_y) - connected_components_list[y] = np.where( - overlap, - 0, - connected_components_list[y], - ) - for x, connected_components in enumerate(connected_components_list): - original_bincount = connected_components_bincounts[x] - count = original_bincount.shape[0] - new_bincount = np.bincount(connected_components.flatten(), minlength=count) - areas_ratio = np.divide( - new_bincount.astype(np.float32), - original_bincount.astype(np.float32), - out=np.ones((count,), dtype=np.float32), - where=original_bincount != 0, - ) - clusters[x] = np.where( - areas_ratio[original_connected_components_list[x]] <= 0.1, - 0, - clusters[x], + background: np.ndarray | None, +) -> np.ndarray: + """Find small regions one color at a time, then use labeled chamfer refill.""" + remove = np.zeros(labels.shape, dtype=bool) + for color in np.unique(labels): + mask = labels == color + _, components = cv2.connectedComponents(mask.astype(np.uint8), connectivity=8) + sizes = np.bincount(components.ravel()) + remove |= mask & (sizes[components] < 8) + if background is not None: + remove &= background == 0 + else: + height, width = labels.shape + edge = {(y, x) for y in (0, height - 1) for x in range(width)} + edge |= {(y, x) for x in (0, width - 1) for y in range(height)} + counts = Counter(int(labels[y, x]) for y, x in edge if not remove[y, x]) + if counts: + color = min(counts, key=lambda value: (-counts[value], value)) + remove &= labels != color + result = labels.copy() + if remove.any() and not remove.all(): + _, nearest = cv2.distanceTransformWithLabels( + remove.astype(np.uint8), + cv2.DIST_L2, + 5, + labelType=cv2.DIST_LABEL_PIXEL, ) - labels = np.zeros(dims).astype(np.uint8) - for cluster in clusters: - labels = np.where(labels == 0, cluster, labels) - return color_quantize.fill_holes(labels) - 1, colors + # OpenCV numbers each zero pixel in scan order, starting from one. + survivors = labels[~remove] + result[remove] = survivors[nearest[remove] - 1] + return result diff --git a/vectorizing/tests/test_color_cleanup.py b/vectorizing/tests/test_color_cleanup.py index adc6576..6ad3452 100644 --- a/vectorizing/tests/test_color_cleanup.py +++ b/vectorizing/tests/test_color_cleanup.py @@ -1,224 +1,113 @@ -"""Cluster cleanup parity, morphology edge cases and component-map lifetime. - -Unfilled comparisons expose the actual keep/remove decisions: hole filling can -otherwise repaint a wrongly removed component and hide the regression. -""" - -import weakref +"""Area-only cleanup preserves thin connected regions and transparent counters.""" import numpy as np import pytest -from vectorizing.solvers.color import quantize as color_quantize -from vectorizing.tests.color_reference import legacy_enhance - -# After the final label shift, an unfilled zero wraps to uint16's maximum. -# This sentinel is used only by tests bypassing fill_holes with a nonempty palette. -UNFILLED_LABEL = np.iinfo(np.uint16).max - - -@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) -@pytest.mark.parametrize( - "variant", - [ - "noise", - "strided", - "one-pixel", - "one-row", - "one-column", - "solid", - "sparse", - "checkerboard", - ], -) -# Transparent artwork can add a background entry to the 64 requested colors. -@pytest.mark.parametrize("color_count", [1, 2, 6, 16, 64, 65]) +from vectorizing.solvers.color.quantize import clean_components +from vectorizing.tests.color_reference import reference_clean_components + + +@pytest.mark.parametrize("count", [1, 2, 6, 16, 64, 65]) +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("strided", [False, True]) @pytest.mark.parametrize("seed", range(3)) -def test_cluster_cleanup_matches_original( - before_fill: bool, - variant: str, - color_count: int, +def test_cleanup_matches_per_color_reference( + count: int, + transparent: bool, + strided: bool, seed: int, - monkeypatch: pytest.MonkeyPatch, ) -> None: - """Preserve component decisions and filled labels without mutating inputs.""" + """Match a separate CCL implementation without changing input storage/dtype.""" rng = np.random.default_rng(seed) - noise = rng.integers(0, color_count, (19, 23), dtype=np.uint8) - labels = { - "noise": noise, - "strided": noise[::2, ::2], - "one-pixel": noise[:1, :1], - "one-row": noise[:1, :], - "one-column": noise[:, :1], - "solid": np.full_like(noise, color_count - 1), - "sparse": noise % 2, - "checkerboard": ( - np.indices(noise.shape).sum(axis=0) % min(color_count, 2) - ).astype(np.uint8), - }[variant] - colors = rng.integers(0, 256, (color_count, 4), dtype=np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) + labels = rng.integers(0, count, (39, 47), dtype=np.uint16) + labels[:5] = 0 # Ensure a survivor even in high-color random cases. + if strided: + labels = labels[::2, ::2] + background = (labels == 0).astype(np.uint8) if transparent else None + original = labels.copy() labels.setflags(write=False) - colors.setflags(write=False) - pixels.setflags(write=False) - original_labels = labels.copy() - if before_fill: - # Compare removal decisions, not just the colors painted over their holes. - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - expected, expected_colors = legacy_enhance(pixels, labels, colors) - actual, actual_colors = color_quantize.enhance(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - np.testing.assert_equal(actual.dtype, expected.dtype) - np.testing.assert_array_equal(actual_colors, expected_colors) - np.testing.assert_equal(actual_colors is colors, True) - np.testing.assert_array_equal(labels, original_labels) - - -@pytest.mark.parametrize("area", [9, 10, 11]) -def test_cluster_cleanup_preserves_inclusive_area_threshold( - area: int, - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Keep a component with 1/9 interior area, but remove 1/10 and 1/11.""" - labels = np.zeros((8, 16), dtype=np.uint8) - # A 2x2 core has one interior pixel at (3, 3). Extending only its top row - # changes the component's total area without adding any interior pixels. - labels[2, 2:area] = 1 - labels[3, 2:4] = 1 - colors = np.zeros((2, 3), dtype=np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - expected = labels.astype(np.uint16) - if area >= 10: - expected[labels == 1] = UNFILLED_LABEL - for cleaner in (legacy_enhance, color_quantize.enhance): - actual, _ = cleaner(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - - -def test_cluster_cleanup_preserves_diagonal_connectivity( - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Treat a 2x2 core and its diagonal thin tail as one removable component.""" - labels = np.zeros((8, 16), dtype=np.uint8) - # Seven tail pixels touch the 4-pixel core only at a corner. With full - # connectivity the combined 11-pixel component has 1/11 interior area; - # with 4-neighbor connectivity the core would incorrectly survive at 1/4. - labels[2:4, 2:4] = 1 - labels[4, 4:11] = 1 - colors = np.zeros((2, 3), dtype=np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - expected = labels.astype(np.uint16) - expected[labels == 1] = UNFILLED_LABEL - for cleaner in (legacy_enhance, color_quantize.enhance): - actual, _ = cleaner(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - - -def test_cluster_cleanup_preserves_dilation_anchor_and_border( - monkeypatch: pytest.MonkeyPatch, -) -> None: - """The 2x2 default anchor spares only the isolated top-left corner pixel.""" - labels = np.zeros((5, 5), dtype=np.uint8) - labels[::4, ::4] = 1 - colors = np.zeros((2, 3), dtype=np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - expected = labels.astype(np.uint16) - expected[labels == 1] = UNFILLED_LABEL - # No upper/left source exists at (0, 0); outside the image is not a color. - expected[0, 0] = 1 - for cleaner in (legacy_enhance, color_quantize.enhance): - actual, _ = cleaner(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - - -@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) -@pytest.mark.parametrize("color_count", [0, 1, 3, 256]) -@pytest.mark.parametrize("dtype", [np.uint8, np.uint16, np.int16]) -def test_cluster_cleanup_preserves_unassigned_labels_and_dtype( - color_count: int, - dtype: type[np.generic], - before_fill: bool, - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Ignore unassigned neighbors and retain existing label-shift overflow behavior.""" - rng = np.random.default_rng(42) - # 255 + 1 wraps only for uint8; do not silently fix that old behavior here. - # Small palettes also leave labels whose pixels must not dilate into others. - labels = rng.choice([0, 1, 2, 3, 254, 255], size=(7, 9)).astype(dtype) - if dtype == np.int16: - labels[1, 1:3] = [-1, -2] - if before_fill: - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - colors = np.zeros((color_count, 3), dtype=np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - expected, _ = legacy_enhance(pixels, labels, colors) - actual, actual_colors = color_quantize.enhance(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - np.testing.assert_equal(actual.dtype, expected.dtype) - np.testing.assert_equal(actual_colors is colors, True) - - -@pytest.mark.parametrize("before_fill", [False, True], ids=["filled", "unfilled"]) -@pytest.mark.parametrize("transpose", [False, True]) -def test_cluster_cleanup_crops_labeling_without_losing_neighbor_influence( - before_fill: bool, - transpose: bool, - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Crop sparse colors while preserving disjoint islands and outside influences.""" - labels = np.zeros((13, 17), dtype=np.uint8) - labels[2:4, 3:5] = 1 - labels[8, 11] = 1 # A disconnected pixel of the same color must be removed. - labels[0, 14:17] = 2 # A single-row crop touching the image border. - labels[9, 2] = labels[10, 3] = 3 # Diagonal contact within a tight crop. - if transpose: - labels = labels.T - colors = np.zeros((6, 3), dtype=np.uint8) # Two palette entries are unused. - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - if before_fill: - monkeypatch.setattr(color_quantize, "fill_holes", lambda matrix: matrix) - expected, _ = legacy_enhance(pixels, labels, colors) - original_label = color_quantize.label - shapes = [] - - def record_label(cluster: np.ndarray, connectivity: int) -> np.ndarray: - shapes.append(cluster.shape) - return original_label(cluster, connectivity=connectivity) - - monkeypatch.setattr(color_quantize, "label", record_label) - actual, _ = color_quantize.enhance(pixels, labels, colors) - np.testing.assert_array_equal(actual, expected) - # The background spans the image; each other color gets one minimal box, - # including all of its disconnected pieces, and unused entries get no pass. - expected_shapes = [(13, 17), (7, 9), (1, 3), (2, 2)] - if transpose: - expected_shapes = [(width, height) for height, width in expected_shapes] - np.testing.assert_array_equal(shapes, expected_shapes) - - -def test_cluster_cleanup_releases_each_component_map( - monkeypatch: pytest.MonkeyPatch, -) -> None: - """Release the old map before labeling the next color, not only on return.""" - original_label = color_quantize.label - maps: list[weakref.ReferenceType[np.ndarray]] = [] - - def record_label(cluster: np.ndarray, connectivity: int) -> np.ndarray: - # Weak references observe lifetime without keeping the maps alive. - # Checking before allocation catches even a temporary two-map overlap. - np.testing.assert_equal(all(ref() is None for ref in maps), True) - components = original_label(cluster, connectivity=connectivity) - maps.append(weakref.ref(components)) - return components - - monkeypatch.setattr(color_quantize, "label", record_label) - labels = (np.indices((8, 9)).sum(axis=0) % 4).astype(np.uint8) - pixels = np.zeros((*labels.shape, 3), dtype=np.uint8) - colors = np.zeros((4, 3), dtype=np.uint8) - color_quantize.enhance(pixels, labels, colors) - # All colors are present: a skipped labeler must not make this pass vacuously. - np.testing.assert_equal(len(maps), 4) - np.testing.assert_equal(all(ref() is None for ref in maps), True) + actual = clean_components(labels, background) + np.testing.assert_array_equal( + actual, + reference_clean_components(labels, background), + ) + np.testing.assert_array_equal(labels, original) + assert actual.dtype == labels.dtype + + +@pytest.mark.parametrize("area", [1, 7, 8, 9, 20]) +def test_thin_components_use_area_not_interior_ratio(area: int) -> None: + """Keep one-pixel-wide features of at least eight pixels, including the cutoff.""" + labels = np.zeros((25, 25), dtype=np.uint16) + labels[10, 2 : 2 + area] = 1 + expected = labels if area >= 8 else np.zeros_like(labels) + np.testing.assert_array_equal(clean_components(labels, None), expected) + + +def test_diagonals_form_one_component() -> None: + """Eight corner-connected pixels survive even though none has an interior.""" + labels = np.zeros((16, 16), dtype=np.uint16) + indices = np.arange(3, 11) + labels[indices, indices] = 1 + np.testing.assert_array_equal(clean_components(labels, None), labels) + + +def test_small_transparent_counter_is_protected() -> None: + """Never remove a background hole, even when it is smaller than the area cutoff.""" + labels = np.ones((16, 16), dtype=np.uint16) + labels[8, 8] = 0 + background = (labels == 0).astype(np.uint8) + np.testing.assert_array_equal(clean_components(labels, background), labels) + + +@pytest.mark.parametrize("area", [1, 4, 7, 8]) +def test_enclosed_opaque_counter_survives(area: int) -> None: + """Protect background-colored counters even below the usual area cutoff.""" + labels = np.zeros((16, 16), dtype=np.uint16) + labels[3:13, 3:13] = 1 + labels[7, 4 : 4 + area] = 0 + np.testing.assert_array_equal(clean_components(labels, None), labels) + + +@pytest.mark.parametrize("shape", [(1, 1), (1, 7), (7, 1), (4, 4)]) +def test_no_survivors_retains_original_labels(shape: tuple[int, int]) -> None: + """Do not feed an all-foreground distance transform when every region is tiny.""" + labels = np.arange(np.prod(shape), dtype=np.uint16).reshape(shape) + np.testing.assert_array_equal(clean_components(labels, None), labels) + + +def test_background_selection_ignores_tiny_perimeter_components() -> None: + """Discard border noise rather than mistaking its frequent color for background.""" + labels = np.ones((20, 20), dtype=np.uint16) + labels[0, ::2] = labels[-1, ::2] = 0 + labels[::2, 0] = labels[::2, -1] = 0 + np.testing.assert_array_equal(clean_components(labels, None), 1) + + +@pytest.mark.parametrize("shape", [(1, 20), (20, 1)]) +def test_background_selection_on_narrow_images(shape: tuple[int, int]) -> None: + """Count each perimeter pixel once on a single row or column.""" + labels = np.array([1] + [2] * 8 + [1] * 11, dtype=np.uint16).reshape(shape) + np.testing.assert_array_equal( + clean_components(labels, None), + reference_clean_components(labels, None), + ) + + +@pytest.mark.parametrize("shape", [(1, 40_000), (40_000, 1)]) +def test_distant_holes_receive_a_surviving_color(shape: tuple[int, int]) -> None: + """The label propagation limit must not invent palette-zero survivors.""" + labels = (np.arange(40_000) % 2).astype(np.uint16) + labels[-8:] = 2 + labels = labels.reshape(shape) + original = labels.copy() + np.testing.assert_array_equal(clean_components(labels, None), 2) + np.testing.assert_array_equal(labels, original) + + +def test_small_island_can_refill_from_transparent_background() -> None: + """Remove tiny opaque specks without painting over transparent pixels.""" + labels = np.zeros((12, 12), dtype=np.uint16) + labels[5, 5] = 1 + background = (labels == 0).astype(np.uint8) + np.testing.assert_array_equal(clean_components(labels, background), 0) diff --git a/vectorizing/tests/test_color_equivalence.py b/vectorizing/tests/test_color_equivalence.py index 2be8255..99f9d8d 100644 --- a/vectorizing/tests/test_color_equivalence.py +++ b/vectorizing/tests/test_color_equivalence.py @@ -1,8 +1,4 @@ -"""Full solver regressions comparing exact SVG bytes, colors and geometry. - -Replace one optimization at a time with its frozen reference while retaining the -others. This catches interactions that isolated mask/centroid/cleanup tests miss. -""" +"""Compare optimized P3 operations with independent references end to end.""" from pathlib import Path from unittest.mock import Mock @@ -17,8 +13,8 @@ from vectorizing.svg.markup import generate_SVG_markup from vectorizing.tests.color_reference import ( legacy_create_bitmaps, - legacy_enhance, legacy_initial_centroids, + reference_clean_components, ) @@ -42,7 +38,7 @@ def test_color_optimizations_preserve_vectorization( optimization: str, monkeypatch: pytest.MonkeyPatch, ) -> None: - """Compare final SVG, colors, dimensions and bounds against the old algorithm.""" + """Compare SVG, colors, dimensions and bounds with independent operation oracles.""" with Image.open(Path(__file__).parent / "images" / image_name) as image: actual = ColorSolver(image, color_count, Timer()).solve() target, legacy = { @@ -55,8 +51,8 @@ def test_color_optimizations_preserve_vectorization( legacy_create_bitmaps, ), "cleanup": ( - "vectorizing.solvers.color.quantize.enhance", - legacy_enhance, + "vectorizing.solvers.color.quantize.clean_components", + reference_clean_components, ), }[optimization] # Patch each lookup site and verify the legacy implementation was used. diff --git a/vectorizing/tests/test_color_layer_artwork.py b/vectorizing/tests/test_color_layer_artwork.py index 217e070..d30624f 100644 --- a/vectorizing/tests/test_color_layer_artwork.py +++ b/vectorizing/tests/test_color_layer_artwork.py @@ -5,13 +5,11 @@ from unittest.mock import Mock import numpy as np -import potrace import pytest from cairosvg import svg2png from PIL import Image from scipy.ndimage import distance_transform_edt -from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.server.timer import Timer from vectorizing.solvers.color.bitmaps import add_bitmap_rims from vectorizing.solvers.color.ColorSolver import ColorSolver @@ -34,9 +32,13 @@ def test_aftermath_retains_holes_when_layers_are_edited( ) -> None: """Keep the exterior transparent and reveal holes, not underpainting, on edits.""" foreground = [] + owned = [] def capture_foreground(masks: list[np.ndarray]) -> None: foreground.append(masks[0].copy()) + for index, mask in enumerate(masks): + above = masks[index + 1] if index + 1 < len(masks) else 0 + owned.append(mask > above) add_bitmap_rims(masks) rim_builder = Mock(side_effect=capture_foreground) @@ -47,11 +49,6 @@ def capture_foreground(masks: list[np.ndarray]) -> None: with Image.open(Path(__file__).parent / "images" / "aftermath.png") as image: paths, colors, width, height = ColorSolver(image, 16, Timer()).solve() rim_builder.assert_called_once() - silhouette = potrace_path_to_compound_path(potrace.Bitmap(foreground[0]).trace()) - silhouette_svg = generate_SVG_markup([silhouette], [[0, 0, 0]], width, height) - silhouette_alpha = np.asarray( - Image.open(BytesIO(svg2png(bytestring=silhouette_svg))).convert("RGBA"), - )[:, :, 3] markup = generate_SVG_markup(paths, colors, width, height) full = np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) np.testing.assert_equal(full[:, :, 3].min(), 0) @@ -60,10 +57,12 @@ def capture_foreground(masks: list[np.ndarray]) -> None: alpha = full[:, :, 3] # Unlike a total partial-alpha budget, this checks where gaps occur. Allow # a 3-pixel band by the exterior: separately fitted curves can differ there. - interior = distance_transform_edt(silhouette_alpha == 255) > 3 + # Use the actual foreground mask: tracing a reference silhouette with + # Potrace's default speck removal would fill genuine tiny background holes. + interior = distance_transform_edt(foreground[0] > 0) > 3 np.testing.assert_equal(interior.any(), True) np.testing.assert_array_equal(alpha[interior], 255) - exterior = distance_transform_edt(silhouette_alpha == 0) > 3 + exterior = distance_transform_edt(foreground[0] == 0) > 3 np.testing.assert_array_equal(alpha[exterior], 0) np.testing.assert_equal( np.count_nonzero((alpha > 0) & (alpha < 255)) < 10_000, @@ -74,10 +73,12 @@ def capture_foreground(masks: list[np.ndarray]) -> None: solo_alpha = np.asarray( Image.open(BytesIO(svg2png(bytestring=solo))).convert("RGBA"), )[:, :, 3] - # Select a point far inside the color, excluding its intentionally narrow rim. - distances = distance_transform_edt(solo_alpha == 255) - np.testing.assert_equal(distances.max() > 2, True) + # Sample actual ownership, not the solo path: many tiny neighboring + # regions can be covered by bounded rims and appear solid in a solo render. + distances = distance_transform_edt(owned[index]) + np.testing.assert_equal(distances.max() > 4, True) point = np.unravel_index(distances.argmax(), distances.shape) + np.testing.assert_equal(solo_alpha[point], 255) for opacity in [None, 0, 0.5]: edited_paths, edited_colors = list(paths), list(colors) if opacity is None: diff --git a/vectorizing/tests/test_color_p3.py b/vectorizing/tests/test_color_p3.py new file mode 100644 index 0000000..73e3dab --- /dev/null +++ b/vectorizing/tests/test_color_p3.py @@ -0,0 +1,252 @@ +"""Acceptance checks for the approved detail-preserving color pipeline.""" + +import hashlib +import json +from io import BytesIO +from pathlib import Path +from unittest.mock import Mock + +import cv2 +import numpy as np +import pytest +from cairosvg import svg2png +from flask.testing import FlaskClient +from pathops import PathOpsError +from PIL import Image + +from vectorizing.geometry.bounds import compound_paths_bounds +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.bitmaps import add_bitmap_rims +from vectorizing.solvers.color.ColorSolver import ColorSolver, trace_bitmap +from vectorizing.solvers.color.quantize import quantize +from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.tests.test_svg_geometry import expected_commands + +IMAGES = Path(__file__).parent / "images" + + +def test_aftermath_matches_approved_p3_geometry( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep approved masks, validated native geometry variants, palette and size.""" + masks = [] + + def capture_rims(bitmaps: list[np.ndarray]) -> None: + add_bitmap_rims(bitmaps) + masks.extend(bitmap.astype(np.uint8).tobytes() for bitmap in bitmaps) + + monkeypatch.setattr( + "vectorizing.solvers.color.ColorSolver.add_bitmap_rims", + capture_rims, + ) + with Image.open(IMAGES / "aftermath.png") as image: + paths, colors, width, height = ColorSolver(image, 8, Timer()).solve() + # Ordered masks are identical across ARM64 and x86_64. Native Potrace makes + # different curve-optimization decisions on those identical inputs. Both + # geometry captures were checked for coverage and composited render error; + # accept only those validated variants, not an arbitrary CI replacement. + assert hashlib.sha256(b"".join(masks)).hexdigest() == ( + "e70cbf1c9d62e8ba853f6fa547975aac8311d9c44ac71decf14e9a6b2bf502bf" + ) + commands = [expected_commands(path) for path in paths] + digest = hashlib.sha256( + json.dumps(commands, separators=(",", ":")).encode(), + ).hexdigest() + assert digest in { + "23d8c97dee23ea3f0b22d164d39f726f36ead7f2ce47048ca73326bf2731c7e8", # ARM64 + "1f52fe3d8589574cc561bf5ab0dff6a9ce410292d79b9e05dcf0a781f2d919f3", # x86_64 + } + np.testing.assert_array_equal( + np.asarray(colors)[:, :3], + [ + [2, 3, 8], + [19, 60, 148], + [28, 100, 202], + [41, 36, 63], + [192, 149, 160], + [213, 54, 118], + [235, 215, 217], + [248, 57, 61], + ], + ) + assert (width, height) == (1024, 1024) + svg = generate_SVG_markup(paths, colors, width, height) + # Approved pre-encoding P3: 1,376,657 bytes. Do not discard geometry for size. + assert len(svg.encode()) < 760_000 + + +@pytest.fixture(scope="module") +def bubbles_pixels() -> np.ndarray: + """Render the real 16-color artwork at its original dimensions.""" + with Image.open(IMAGES / "bubbles.png") as image: + result = ColorSolver(image, 16, Timer()).solve() + png = svg2png( + bytestring=generate_SVG_markup(*result), + output_width=image.width, + output_height=image.height, + ) + return np.asarray(Image.open(BytesIO(png)).convert("RGBA")) + + +@pytest.mark.parametrize("threshold", [15, 30, 45]) +@pytest.mark.parametrize( + "box, center, minimum_area", + [((697, 891, 736, 933), (19, 21), 15), ((752, 868, 786, 899), (17, 15), 5)], + ids=["a", "e"], +) +def test_laundry_care_counters_remain_open( + bubbles_pixels: np.ndarray, + threshold: int, + box: tuple[int, int, int, int], + center: tuple[int, int], + minimum_area: int, +) -> None: + """Retain both enclosed light counters, including the smaller 'e'.""" + x0, y0, x1, y1 = box + roi = bubbles_pixels[y0:y1, x0:x1, :3].astype(np.int16) + pink = (roi[:, :, 0] - roi[:, :, 1] > threshold) & ( + roi[:, :, 0] - roi[:, :, 2] > threshold / 2 + ) + _, components, stats, centers = cv2.connectedComponentsWithStats( + (~pink).astype(np.uint8), + connectivity=8, + ) + border = np.unique( + np.concatenate( + [ + components[0], + components[-1], + components[:, 0], + components[:, -1], + ], + ), + ) + holes = [ + index + for index in range(1, len(stats)) + if index not in border + and stats[index, cv2.CC_STAT_AREA] >= minimum_area + and np.linalg.norm(centers[index] - center) <= 6 + ] + assert holes, f"The Laundry Care counter at {box} was filled" + + +@pytest.mark.parametrize( + "count, expected", + [(None, 6), (0, 6), (1, 2), (8, 8), (100, 64)], +) +def test_public_limits_remain_unchanged(count: int | None, expected: int) -> None: + """Keep caller color counts/defaults and the existing pixel-area cap.""" + solver = ColorSolver(Image.new("RGB", (1200, 1200)), count, Timer()) + assert solver.color_count == expected + assert solver.img.size == (1024, 1024) + + +def test_canvas_padding_is_clipped_from_returned_paths() -> None: + """Fill canvas corners without exposing padding in exported geometry or bounds.""" + path = trace_bitmap(np.ones((12, 20), dtype=np.uint8)) + assert compound_paths_bounds([path]) == { + "left": 0, + "top": 0, + "right": 20, + "bottom": 12, + "width": 20, + "height": 12, + } + png = svg2png(bytestring=generate_SVG_markup([path], [[0, 0, 0]], 20, 12)) + np.testing.assert_array_equal( + np.asarray(Image.open(BytesIO(png)).convert("RGBA"))[:, :, 3], + 255, + ) + + +@pytest.mark.parametrize("raw", [False, True]) +def test_clip_failure_retraces_bounded_vectors( + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, + caplog: pytest.LogCaptureFixture, + raw: bool, +) -> None: + """An exceptional clip failure still yields smooth vectors, holes and bounds.""" + pixels = np.full((20, 32, 4), 255, dtype=np.uint8) + pixels[8:12, 14:18, 3] = 0 + monkeypatch.setattr( + "vectorizing.try_read_image_from_url", + lambda url: Image.fromarray(pixels), + ) + clip = Mock(side_effect=PathOpsError("injected failure")) + monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.op", clip) + upload = Mock(return_value="fallback-svg") + monkeypatch.setattr("vectorizing.upload_markup", upload) + response = client.post("/", json={"url": "unused", "solver": 1, "raw": raw}) + assert response.status_code == 200 + clip.assert_called_once() + assert "retracing without padding" in caplog.text + if raw: + markup = response.data + upload.assert_not_called() + else: + upload.assert_called_once() + markup = upload.call_args.args[0] + bounds = response.get_json()["info"]["bounds"] + assert 0 <= bounds["left"] <= bounds["right"] <= 32 + assert 0 <= bounds["top"] <= bounds["bottom"] <= 20 + rendered = np.asarray( + Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA"), + ) + assert rendered[10, 16, 3] == 0 + assert rendered[5, 5, 3] == 255 + + +def test_clip_recovery_constrains_curve_overshoot( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Unpadded curve fitting can still extend beyond the bitmap's control hull.""" + rng = np.random.default_rng(6) + height, width = rng.integers(1, 45, 2) + mask = (rng.random((height, width)) < rng.uniform(0.03, 0.98)).astype(np.uint8) + clip = Mock(side_effect=PathOpsError("injected failure")) + monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.op", clip) + path = trace_bitmap(mask) + clip.assert_called_once() + for _, points in path: + for x, y in points: + assert 0 <= x <= width + assert 0 <= y <= height + + +def test_clipped_logo_preserves_opaque_canvas() -> None: + """Keep coverage on a real clipped logo, including the canvas boundary.""" + with Image.open(IMAGES / "geo_logo.png") as image: + result = ColorSolver(image, 8, Timer()).solve() + markup = generate_SVG_markup(*result) + png = svg2png(bytestring=markup) + pixels = np.asarray(Image.open(BytesIO(png)).convert("RGBA")) + np.testing.assert_array_equal(pixels[:, :, 3], 255) + + +def test_clipped_consecutive_quadratics_keep_opaque_coverage() -> None: + """Real clipping must not emit malformed Q commands that expose transparent gaps.""" + rng = np.random.default_rng(513) + height, width = rng.integers(1, 45, 2) + mask = rng.random((height, width)) < rng.uniform(0.03, 0.98) + pixels = np.full((height, width, 3), 255, dtype=np.uint8) + pixels[mask] = [255, 0, 0] + result = ColorSolver(Image.fromarray(pixels), 2, Timer()).solve() + rendered = np.asarray( + Image.open( + BytesIO(svg2png(bytestring=generate_SVG_markup(*result))), + ).convert("RGBA"), + ) + assert rendered[:, :, 3].min() >= 240 + + +def test_fully_transparent_image_has_no_foreground() -> None: + """Area cleanup must not invent opaque pixels in an entirely transparent input.""" + pixels = np.zeros((8, 8, 4), dtype=np.uint8) + labels, palette, background = quantize(pixels, 16) + assert background + np.testing.assert_array_equal(labels, 0) + assert palette.dtype == np.uint8 + result = ColorSolver(Image.fromarray(pixels), 16, Timer()).solve() + assert result[0] == [] diff --git a/vectorizing/tests/test_integration.py b/vectorizing/tests/test_integration.py index 8cb8231..3f74b3f 100644 --- a/vectorizing/tests/test_integration.py +++ b/vectorizing/tests/test_integration.py @@ -107,19 +107,24 @@ def test_color_solver_preserves_empty_transparent_image() -> None: assert rendered.getchannel("A").getextrema() == (0, 0) -def test_uploads_markup_to_s3(client: FlaskClient) -> None: +@pytest.mark.parametrize("solver", [0, 1]) +def test_uploads_markup_to_s3(client: FlaskClient, solver: int) -> None: """Store the generated SVG with its media type and return the object's key.""" response = client.post( "/", json={ "url": get_image_url("black_rectangle.png"), - "solver": 0, + "solver": solver, "raw": False, }, ) assert response.status_code == 200 payload = response.get_json() + info = payload["info"] + bounds = info["bounds"] + assert 0 <= bounds["left"] <= bounds["right"] <= info["image_width"] + assert 0 <= bounds["top"] <= bounds["bottom"] <= info["image_height"] test_bucket = os.environ["S3_TEST_BUCKET"] s3 = get_s3_client() try: diff --git a/vectorizing/tests/test_svg_geometry.py b/vectorizing/tests/test_svg_geometry.py new file mode 100644 index 0000000..c4f913d --- /dev/null +++ b/vectorizing/tests/test_svg_geometry.py @@ -0,0 +1,196 @@ +"""Decode compact paths independently to verify exact two-decimal geometry.""" + +import re +from decimal import Decimal +from io import BytesIO + +import numpy as np +import pytest +from cairosvg import svg2png +from defusedxml import ElementTree as ET +from pathops import Path +from PIL import Image + +from vectorizing.svg.markup import generate_SVG_markup + +SVG = "{http://www.w3.org/2000/svg}" + + +def decode_path(data: str) -> list[tuple[str, tuple[int, ...]]]: + """Expand SVG's integer path grammar to absolute M/L/Q/C/Z commands.""" + tokens = re.findall(r"[A-Za-z]|-?\d+", data) + result = [] + cursor = np.array([0, 0], dtype=np.int64) + origin = cursor.copy() + control = None + command = "" + i = 0 + while i < len(tokens): + if tokens[i].isalpha(): + command = tokens[i] + i += 1 + kind = command.upper() + if kind == "Z": + result.append(("Z", ())) + cursor = origin.copy() + control = None + command = "" + continue + count = {"M": 2, "L": 2, "H": 1, "V": 1, "Q": 4, "C": 6, "S": 4}[kind] + values = np.array(tokens[i : i + count], dtype=np.int64) + i += count + if kind in ("H", "V"): + axis = int(kind == "V") + point = cursor.copy() + point[axis] = values[0] + (cursor[axis] if command.islower() else 0) + points = point.reshape(1, 2) + kind = "L" + else: + points = values.reshape(-1, 2) + if command.islower(): + points = points + cursor + if kind == "S": + reflected = cursor if control is None else 2 * cursor - control + points = np.vstack([reflected, points]) + kind = "C" + result.append((kind, tuple(int(n) for n in points.ravel()))) + cursor = points[-1].copy() + control = points[-2].copy() if kind == "C" else None + if kind == "M": + origin = cursor.copy() + command = "l" if command.islower() else "L" + return result + + +def expected_commands(path: Path) -> list[tuple[str, tuple[int, ...]]]: + """Use decimal arithmetic on the original segments, not encoder helpers.""" + expanded = [] + for kind, points in path.segments: + if kind == "qCurveTo": + # Independently expand the segment-pen's implied on-curve midpoints; + # production uses raw PathVerb pairs instead of this interface. + for index, control in enumerate(points[:-1]): + endpoint = points[-1] + if index < len(points) - 2: + endpoint = tuple( + (a + b) / 2 for a, b in zip(control, points[index + 1]) + ) + expanded.append(("Q", (control, endpoint))) + else: + command = { + "moveTo": "M", + "lineTo": "L", + "curveTo": "C", + "closePath": "Z", + }[kind] + expanded.append((command, points)) + return [ + ( + command, + tuple(int(Decimal(f"{n:.2f}") * 100) for point in points for n in point), + ) + for command, points in expanded + ] + + +@pytest.mark.parametrize("seed", range(30)) +def test_random_compound_paths_round_trip(seed: int) -> None: + """Preserve every point and closed subpath through mixed relative commands.""" + rng = np.random.default_rng(seed) + path = Path() + for _ in range(5): + path.moveTo(*rng.uniform(-2000, 2000, 2)) + for index in range(20): + if index % 3 == 1: + path.cubicTo(*rng.uniform(-2000, 2000, 6)) + elif index % 3 == 2: + path.quadTo(*rng.uniform(-2000, 2000, 4)) + else: + path.lineTo(*rng.uniform(-2000, 2000, 2)) + path.close() + root = ET.fromstring(generate_SVG_markup([path], [[12, 34, 56]], 1024, 900)) + assert root.attrib == {"width": "1024", "height": "900", "viewBox": "0 0 1024 900"} + assert root.find(f"{SVG}g").get("transform") == "scale(.01)" + assert decode_path(root.find(f".//{SVG}path").get("d")) == expected_commands(path) + + +def test_axes_reflections_and_close_reset() -> None: + """Cover H/V/S, implicit repeats and relative moves after a closed subpath.""" + path = Path() + path.moveTo(100, 100) + path.lineTo(101, 100) + path.lineTo(101, 102) + path.cubicTo(101, 103, 102, 104, 103, 104) + path.cubicTo(104, 104, 105, 103, 105, 102) + path.cubicTo(105, 101, 104, 100, 103, 100) + path.close() + path.moveTo(101, 101) + path.lineTo(101.25, 101.25) + path.lineTo(102.25, 102.25) + path.close() + markup = generate_SVG_markup([path], [[0, 0, 0]], 200, 200) + data = ET.fromstring(markup).find(f".//{SVG}path").get("d") + assert all(command in data.lower() for command in "hvsmz") + assert decode_path(data) == expected_commands(path) + + +def test_consecutive_quadratics_expand_implied_endpoints() -> None: + """Skia's segment pen can combine two quadratics into three coordinate pairs.""" + path = Path() + path.moveTo(1, 1) + path.quadTo(2, 3, 4, 4) + path.quadTo(6, 5, 7, 7) + path.close() + assert len(list(path.segments)[1][1]) == 3 + markup = generate_SVG_markup([path], [[0, 0, 0]], 10, 10) + data = ET.fromstring(markup).find(f".//{SVG}path").get("d") + assert decode_path(data) == [ + ("M", (100, 100)), + ("Q", (200, 300, 400, 400)), + ("Q", (600, 500, 700, 700)), + ("Z", ()), + ] + + +def test_rounding_near_half_ties_and_negative_zero() -> None: + """Retain legacy decimal rounding instead of rounding multiplied binary floats.""" + path = Path() + path.moveTo(-0.0, 2.675) + path.cubicTo(-2.675, 1.005, 9.995, -0.005, 1000.125, 1.235) + path.close() + markup = generate_SVG_markup([path], [[255, 0, 0]], 1200, 1200) + data = ET.fromstring(markup).find(f".//{SVG}path").get("d") + assert decode_path(data) == expected_commands(path) + assert 'fill="#f00"' in markup + + +@pytest.mark.parametrize("size", [40, 101, 160]) +def test_compound_hole_rendering(size: int) -> None: + """Keep holes, transparent exterior and half opacity after transformed encoding.""" + path = Path() + path.moveTo(4, 4) + path.lineTo(36, 4) + path.lineTo(36, 36) + path.lineTo(4, 36) + path.close() + # Opposite winding carves a hole in the same compound path. + path.moveTo(12, 12) + path.lineTo(12, 28) + path.lineTo(28, 28) + path.lineTo(28, 12) + path.close() + svg = generate_SVG_markup([path], [[20, 30, 40, 0.5]], 40, 40) + pixels = np.asarray( + Image.open( + BytesIO( + svg2png( + bytestring=svg, + output_width=size, + output_height=size, + ), + ), + ).convert("RGBA"), + ) + assert pixels[size // 2, size // 2, 3] == 0 + assert pixels[0, 0, 3] == 0 + assert pixels[size // 5, size // 5, 3] == 128 diff --git a/vectorizing/tests/test_svg_markup.py b/vectorizing/tests/test_svg_markup.py index 31e2e80..55c4624 100644 --- a/vectorizing/tests/test_svg_markup.py +++ b/vectorizing/tests/test_svg_markup.py @@ -1,4 +1,4 @@ -"""Freeze externally visible SVG formatting, including whitespace and alpha.""" +"""Freeze compact SVG spelling while preserving coordinate rounding and alpha.""" from collections.abc import Sequence @@ -42,7 +42,7 @@ def test_color_formatting(color: Sequence[float] | np.ndarray, expected: str) -> def test_svg_serialization_preserves_exact_markup() -> None: - """Keep paint order, empty-path filtering, cubic syntax and document whitespace.""" + """Keep paint order, empty-path filtering, viewport and fractional alpha.""" curve = Path() curve.moveTo(0, 0) curve.lineTo(10, 0) @@ -60,17 +60,16 @@ def test_svg_serialization_preserves_exact_markup() -> None: ) assert actual == ( '\n' - '\n\n' - '\n' - "\n" + 'viewBox="0 0 40 20">' + '' + '' + "" ) def test_empty_svg_serialization() -> None: - """Keep the empty document's dimensions and blank group unchanged.""" + """Keep the empty document's dimensions and omit all paint.""" assert generate_SVG_markup([], [], 8, 9) == ( '\n\n\n\n' + 'viewBox="0 0 8 9">' ) From 31e9568071fc9f34650fb787138b44b49779b802 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Mon, 28 Sep 2026 13:26:13 +0200 Subject: [PATCH 13/16] fix: preserve line weight when deleting detected backgrounds (#86) * fix: preserve line weight when deleting detected backgrounds Isolate only opaque, uniform-perimeter backgrounds painted above every foreground color. Keep their overlap bounded and preserve foreground order and tracing. Unsupported cases remain unchanged, and PathOps failures retain the complete original layer set. Add customer artwork and deletion, opacity, counter, palette-guard and API recovery regressions. Validated with 733 tests, all pre-commit hooks, 126 focused x86-64 checks and 29 exact prototype comparisons. * chore: keep background fix PR focused on code and tests --- vectorizing/solvers/color/ColorSolver.py | 30 ++- vectorizing/solvers/color/bitmaps.py | 34 +++ vectorizing/tests/images/midnight_strike.png | Bin 0 -> 1205449 bytes vectorizing/tests/test_color_background.py | 197 ++++++++++++++++++ .../tests/test_color_layer_ownership.py | 117 +++++++++++ 5 files changed, 375 insertions(+), 3 deletions(-) create mode 100644 vectorizing/tests/images/midnight_strike.png create mode 100644 vectorizing/tests/test_color_background.py create mode 100644 vectorizing/tests/test_color_layer_ownership.py diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index a4382af..c91a015 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -9,7 +9,11 @@ from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.server.timer import Timer -from vectorizing.solvers.color.bitmaps import add_bitmap_rims, create_bitmaps +from vectorizing.solvers.color.bitmaps import ( + add_bitmap_rims, + create_background_bitmap, + create_bitmaps, +) from vectorizing.solvers.color.quantize import quantize from vectorizing.util.limit_size import limit_size @@ -20,8 +24,8 @@ def _trace_mask(bitmap: np.ndarray) -> Path: return potrace_path_to_compound_path(traced) -def trace_bitmap(bitmap: np.ndarray) -> Path: - """Trace detail without speck removal, extending then clipping canvas edges.""" +def trace_bitmap(bitmap: np.ndarray, *, recover_clip: bool = True) -> Path: + """Trace bounded detail, optionally leaving clip recovery to the caller.""" height, width = bitmap.shape # Potrace rounds exposed mask corners. Extending edge labels moves that # rounding outside the viewport instead of leaving transparent canvas corners. @@ -41,6 +45,8 @@ def trace_bitmap(bitmap: np.ndarray) -> Path: try: path = op(path, canvas, PathOp.INTERSECTION) except PathOpsError: + if not recover_clip: + raise # Recovery keeps smooth, bounded vectors and does not repeat the # failing boolean operation. Unpadded tracing can round canvas # corners inward; only this exceptional layer loses edge coverage. @@ -84,12 +90,30 @@ def solve(self) -> list[list[Path] | list[np.ndarray] | int]: self.timer.end_timer() self.timer.start_timer("Bitmap Creation") + background_bitmap = create_background_bitmap(labels, colors, has_background) bitmaps, colors = create_bitmaps(labels, colors, has_background) add_bitmap_rims(bitmaps) self.timer.end_timer() self.timer.start_timer("Bitmap Tracing") compound_paths = [trace_bitmap(bitmap) for bitmap in bitmaps] + if background_bitmap is not None: + try: + background = trace_bitmap(background_bitmap, recover_clip=False) + foreground = [ + op(path, compound_paths[-1], PathOp.DIFFERENCE) + for path in compound_paths[:-1] + ] + except PathOpsError: + # Keep the complete original output if any isolation step fails; + # never publish only the foreground colors processed so far. + logging.getLogger(__name__).warning( + "Background isolation failed; retaining original layers", + exc_info=True, + ) + else: + compound_paths = [background, *foreground] + colors = [colors[-1], *colors[:-1]] self.timer.end_timer() return [compound_paths, colors, self.img.size[0], self.img.size[1]] diff --git a/vectorizing/solvers/color/bitmaps.py b/vectorizing/solvers/color/bitmaps.py index a099366..4a730bd 100644 --- a/vectorizing/solvers/color/bitmaps.py +++ b/vectorizing/solvers/color/bitmaps.py @@ -3,6 +3,40 @@ import cv2 import numpy as np +from vectorizing.solvers.color.quantize import _perimeter + + +def create_background_bitmap( + labels: np.ndarray, + colors: np.ndarray, + has_background: bool, +) -> np.ndarray | None: + """Find a frontmost opaque background and give it a bounded two-pixel rim.""" + # The quantizer's background flag means detected transparency. Preserve that + # classification, including its existing handling of partial input alpha. + if has_background: + return None + border = _perimeter(labels) + background = int(border[0]) + if not np.all(border == background): + return None + used = np.unique(labels) + # Intermediate backgrounds have hidden rims beneath later foreground colors; + # cutting those rims can break coverage. Already-first backgrounds need no fix. + if len(used) < 2 or background != used[-1]: + return None + if ( + np.count_nonzero(np.all(colors[used, :3] == colors[background, :3], axis=1)) + != 1 + ): + return None + return cv2.dilate( + (labels == background).astype(np.uint8), + np.ones((5, 5), dtype=np.uint8), + borderType=cv2.BORDER_CONSTANT, + borderValue=0, + ) + def create_bitmaps( labels: np.ndarray, diff --git a/vectorizing/tests/images/midnight_strike.png b/vectorizing/tests/images/midnight_strike.png new file mode 100644 index 0000000000000000000000000000000000000000..8e3f0adb9f4566f9d1235c7167d8ab90ddcfd20a GIT binary patch literal 1205449 zcmV(tK00961NklW~Bqjm`NX!HRb40v%&+ZTIYp=EaKBzAY@$Nl?`ySWczTJT8KV4puX=%!5M?lKwt zWc9?Ba?%lXhM(LM*sMS2bvNoaYcB$k<6O?`u+1I=NCcAfAc3T2ti3&fO~-L`Ves!h zr4qCM%k}59W9xroTdp%&)m2o(8S_jgG9*bB-3$A05Q2wYm1VYcFJ~S7*i@m z=j@NRMOnFF7SFD~C>~>@Jfr$54`}k3_e_}#dq|y|{t=nTpbP@0;Bpk%X^b`^B#YTE 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z`R~u$=(%e-9hSd7?CDSRn3_+jn8LmjoO`g(V+|9X`q?Y7yN9^;@$vi|$y%~B`+Ys* z(+%Js%TTC^(cT?3fPd<=!({RLyB=0u4)f06&p-trXHn}3ng8tBEN-Kdj%XFMyf>@j zagu&oX`%iYjeZLE>lrfdNXI{PpndKdl+GZhT)o*|Oe{}8M!7M>%{MGP2)l)arDstS z2i)a1+w1xa@(|~|;xrwri3Gg>;=x=uEj@+))0?mg9^CQs;JhtL?LzN!H-Y2W{Fko- z-ZBcv@B0NR&mWyu|IfyQ*I0|=m-RII9bcF?5-Hj|KWMA`!* z!^Fsw@1ae9?2lj2<_(~DUM8$H2(5{$SfNsTePIa=(ADTGi9-I+{m=aU^ua7;4NUao zg;pGhsa7=WYzfn~5wAzDwr@;a(Pm$85I(YLGrea)@*CEq4XZsXc#Zqc`8y`g+v~bA0E7ylU!~dE0|H^)(+#@5lDUb9|Z))zq0& zKd7p6k@CsMP+J)*{Zr1v@9d>7T|S2hp|Ses->S=&pWXh_ruQvi!p@8n4RdRQ#;_x= tuple[np.ndarray, np.ndarray]: + """Provide two foreground colors surrounded by a frontmost white background.""" + labels = np.full((40, 40), 2, dtype=np.uint16) + labels[5:35, 8:14] = 0 + labels[8:32, 20:36] = 1 + palette = np.array([[20, 80, 200], [230, 130, 20], [255, 255, 255]], np.uint8) + return labels, palette + + +def test_background_mask_is_bounded_and_does_not_mutate_inputs( + background_labels: tuple[np.ndarray, np.ndarray], +) -> None: + """Match an independent square-neighborhood expansion, not full underpainting.""" + labels, palette = background_labels + original_labels, original_palette = labels.copy(), palette.copy() + expected = np.zeros(labels.shape, dtype=np.uint8) + for y, x in np.argwhere(labels == 2): + expected[max(0, y - 2) : y + 3, max(0, x - 2) : x + 3] = 1 + actual = create_background_bitmap(labels, palette, False) + np.testing.assert_array_equal(actual, expected) + assert actual.dtype == np.uint8 + assert actual[20, 28] == 0 + np.testing.assert_array_equal(labels, original_labels) + np.testing.assert_array_equal(palette, original_palette) + + +@pytest.mark.parametrize( + "case", + ["transparent", "mixed-border", "first", "middle", "duplicate", "single"], +) +def test_unsupported_backgrounds_keep_the_original_svg( + background_labels: tuple[np.ndarray, np.ndarray], + monkeypatch: pytest.MonkeyPatch, + case: str, +) -> None: + """Use the pre-isolation tracing sequence as the unchanged-output oracle.""" + labels, palette = background_labels + transparent = case == "transparent" + if case == "mixed-border": + labels[0, 10] = 0 + elif case == "first": + order = np.array([2, 0, 1]) + labels, palette = np.argsort(order)[labels], palette[order] + elif case == "middle": + order = np.array([0, 2, 1]) + labels, palette = np.argsort(order)[labels], palette[order] + elif case == "duplicate": + palette[0] = palette[2] + elif case == "single": + labels.fill(2) + assert create_background_bitmap(labels, palette, transparent) is None + masks, retained = create_bitmaps(labels, palette, transparent) + add_bitmap_rims(masks) + expected = generate_SVG_markup( + [trace_bitmap(mask) for mask in masks], + retained, + 40, + 40, + ) + paths, colors = trace_layers(monkeypatch, labels, palette, transparent) + assert generate_SVG_markup(paths, colors, 40, 40) == expected + + +def test_detection_uses_only_retained_palette_entries( + background_labels: tuple[np.ndarray, np.ndarray], +) -> None: + """Ignore unused higher colors, and recognize an already-first retained color.""" + labels, palette = background_labels + palette = np.vstack([palette, [255, 255, 255]]).astype(np.uint8) + assert create_background_bitmap(labels, palette, False) is not None + labels[labels != 2] = 3 + assert create_background_bitmap(labels, palette, False) is None + + +def test_detection_supports_the_full_palette_range() -> None: + """Keep 64-color labels intact while finding the frontmost border color.""" + palette = np.array([[i, i * 3 % 256, i * 17 % 256] for i in range(64)], np.uint8) + labels = np.full((12, 12), 63, dtype=np.uint16) + labels[2:10, 2:10] = np.arange(64).reshape(8, 8) + mask = create_background_bitmap(labels, palette, False) + assert mask is not None + assert labels.dtype == np.uint16 + assert len(np.unique(labels)) == 64 + + +@pytest.mark.parametrize("size", [1, 2, 3, 5]) +def test_isolated_background_preserves_counters_and_boundedness( + background_labels: tuple[np.ndarray, np.ndarray], + monkeypatch: pytest.MonkeyPatch, + size: int, +) -> None: + """Keep small background-colored counters open without a full background fill.""" + labels, palette = background_labels + labels[12 : 12 + size, 24 : 24 + size] = 2 + paths, colors = trace_layers(monkeypatch, labels, palette, False) + np.testing.assert_array_equal(colors, palette[[2, 0, 1]]) + assert not paths[0].contains((28, 27)) + assert all(not path.contains((24 + size / 2, 12 + size / 2)) for path in paths[1:]) + assert all(0 <= v <= 40 for path in paths for v in path.bounds) + assert render_layers(paths, colors)[:, :, 3].min() >= 240 + + +def test_partial_alpha_uses_existing_transparency_classification( + background_labels: tuple[np.ndarray, np.ndarray], +) -> None: + """Do not introduce a stricter input-alpha rule than the current quantizer.""" + labels, palette = background_labels + rgba = np.dstack([palette[labels], np.full(labels.shape, 255, np.uint8)]) + rgba[0, 0, 3] = 217 + result = ColorSolver(Image.fromarray(rgba), 3, Timer()).solve() + assert isinstance(result, list) + np.testing.assert_array_equal(result[1][0], palette[2]) + + +@pytest.mark.parametrize("failure", ["background-clip", "second-difference"]) +@pytest.mark.parametrize("raw", [False, True]) +def test_isolation_failure_retains_complete_original_output( + background_labels: tuple[np.ndarray, np.ndarray], + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, + caplog: pytest.LogCaptureFixture, + failure: str, + raw: bool, +) -> None: + """Recover the full original layer set and API response, never partial isolation.""" + labels, palette = background_labels + masks, retained = create_bitmaps(labels, palette, False) + add_bitmap_rims(masks) + expected = generate_SVG_markup( + [trace_bitmap(mask) for mask in masks], + retained, + 40, + 40, + ) + monkeypatch.setattr( + "vectorizing.try_read_image_from_url", + lambda url: Image.fromarray(palette[labels]), + ) + monkeypatch.setattr( + "vectorizing.solvers.color.ColorSolver.quantize", + Mock(return_value=(labels, palette, False)), + ) + # Of the original layers, only the background touches the canvas. Its clip + # succeeds; fail either the new background's clip or a later subtraction. + intersections = [] + differences = [] + + def controlled_op(*args: object, **kwargs: object) -> object: + if args[2] == PathOp.INTERSECTION: + intersections.append(1) + if failure == "background-clip" and len(intersections) == 2: + raise PathOpsError("injected background clip failure") + if args[2] == PathOp.DIFFERENCE: + differences.append(1) + if failure == "second-difference" and len(differences) == 2: + raise PathOpsError("injected subtraction failure") + return op(*args, **kwargs) + + monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.op", controlled_op) + upload = Mock(return_value="original-layers") + monkeypatch.setattr("vectorizing.upload_markup", upload) + response = client.post("/", json={"url": "unused", "solver": 1, "raw": raw}) + assert response.status_code == 200 + if raw: + markup = response.data.decode() + upload.assert_not_called() + else: + upload.assert_called_once() + markup = upload.call_args.args[0] + assert response.get_json()["objectId"] == "original-layers" + assert markup == expected + assert "Background isolation failed; retaining original layers" in caplog.text + assert "retracing without padding" not in caplog.text + assert len(intersections) == 2 + assert len(differences) == (2 if failure == "second-difference" else 0) diff --git a/vectorizing/tests/test_color_layer_ownership.py b/vectorizing/tests/test_color_layer_ownership.py new file mode 100644 index 0000000..d7e6080 --- /dev/null +++ b/vectorizing/tests/test_color_layer_ownership.py @@ -0,0 +1,117 @@ +"""Background deletion must preserve the visible artwork, not every color's rim.""" + +from io import BytesIO +from pathlib import Path + +import numpy as np +import pytest +from cairosvg import svg2png +from defusedxml import ElementTree +from PIL import Image + +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.tests.test_color_layers import trace_layers + + +def edit_background(markup: str, opacity: float | None = None) -> bytes: + """Delete or change the first color node in the emitted SVG itself.""" + document = ElementTree.fromstring(markup) + container = document.find("{http://www.w3.org/2000/svg}g") + assert container is not None + background = list(container)[0] + if opacity is None: + container.remove(background) + else: + background.set("opacity", str(opacity)) + return ElementTree.tostring(document) + + +def raster(markup: str | bytes, scale: float = 1) -> Image.Image: + """Render the SVG on a transparent surface at the requested scale.""" + return Image.open(BytesIO(svg2png(bytestring=markup, scale=scale))).convert("RGBA") + + +@pytest.fixture(scope="module", params=[3, 4, 6, 8, 16]) +def customer_svg(request: pytest.FixtureRequest) -> tuple[str, tuple[int, ...]]: + """Solve the customer image once per palette with real quantization and tracing.""" + filename = Path(__file__).parent / "images" / "midnight_strike.png" + with Image.open(filename) as image: + paths, colors, width, height = ColorSolver( + image, + request.param, + Timer(), + ).solve() + # On this fixture the cream background is the last RGB-ordered color, not + # the first foreground color. It must become the first emitted layer. + background = tuple(int(value) for value in colors[0]) + assert background == max(tuple(int(value) for value in color) for color in colors) + assert len(colors) <= request.param + assert (width, height) == (1024, 1024) + return generate_SVG_markup(paths, colors, width, height), (*background, 255) + + +@pytest.mark.parametrize("scale", [1, 2]) +def test_customer_background_deletion_preserves_artwork( + customer_svg: tuple[str, tuple[int, ...]], + scale: int, +) -> None: + """Preserve appearance on the same matte, with opaque assembly and no new seams.""" + markup, color = customer_svg + full = raster(markup, scale) + removed = raster(edit_background(markup), scale) + zero = raster(edit_background(markup, 0), scale) + assert np.asarray(full)[:, :, 3].min() >= 240 + np.testing.assert_array_equal(np.asarray(removed), np.asarray(zero)) + before = Image.new("RGBA", full.size, color) + before.alpha_composite(full) + after = Image.new("RGBA", full.size, color) + after.alpha_composite(removed) + # Source-over rounding is not pixel-exact. A large hidden foreground lip + # produces differences of hundreds, not these few channel levels. + difference = np.abs(np.asarray(before).astype(np.int16) - np.asarray(after)) + assert difference.max() <= 4 + assert "stroke=" not in markup + assert 'shape-rendering="crispEdges"' not in markup + + +@pytest.mark.parametrize("scale", [1, 1.25, 2]) +def test_thin_line_keeps_its_width_after_background_deletion( + monkeypatch: pytest.MonkeyPatch, + scale: float, +) -> None: + """A six-pixel line stays six pixels wide rather than exposing a four-pixel lip.""" + labels = np.full((40, 40), 2, dtype=np.uint16) + labels[5:35, 8:14] = 0 + labels[8:32, 22:36] = 1 + palette = np.array([[20, 80, 200], [230, 130, 20], [255, 255, 255]], np.uint8) + paths, colors = trace_layers(monkeypatch, labels, palette, False) + np.testing.assert_array_equal(colors, palette[[2, 0, 1]]) + markup = generate_SVG_markup(paths, colors, 40, 40) + full = raster(markup, scale) + removed = raster(edit_background(markup), scale) + assert np.asarray(full)[:, :, 3].min() >= 240 + row = np.asarray(removed)[int(20 * scale), : int(20 * scale), 3] + if scale == 1: + assert np.flatnonzero(row > 128).tolist() == list(range(8, 14)) + expected = Image.new("RGBA", full.size, (255, 255, 255, 255)) + expected.alpha_composite(removed) + difference = np.abs(np.asarray(full).astype(np.int16) - np.asarray(expected)) + assert difference.max() <= 4 + + +def test_background_half_opacity_does_not_fade_foreground( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Keep a single editable background color and normal path-opacity behavior.""" + labels = np.full((40, 40), 2, dtype=np.uint16) + labels[10:30, 10:30] = 0 + labels[15:25, 25:35] = 1 + palette = np.array([[20, 80, 200], [230, 130, 20], [255, 255, 255]], np.uint8) + paths, colors = trace_layers(monkeypatch, labels, palette, False) + markup = generate_SVG_markup(paths, colors, 40, 40) + pixels = np.asarray(raster(edit_background(markup, 0.5))) + assert pixels[2, 2, 3] == 128 + np.testing.assert_array_equal(pixels[20, 15], [20, 80, 200, 255]) + np.testing.assert_array_equal(pixels[20, 30], [230, 130, 20, 255]) From 2c6b730a7166bb1ea8e6d4c88d70bb13c57fc9b3 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Mon, 28 Sep 2026 16:24:26 +0200 Subject: [PATCH 14/16] fix(color): restore original vectorization as default (#87) * fix(color): restore original vectorization as default * style: format color configuration tests --- AGENTS.md | 29 ++- README.md | 23 ++- scripts/_vectorization.py | 26 ++- scripts/benchmark_vectorization.py | 58 +++++- scripts/vectorization_outputs.py | 9 +- vectorizing/__init__.py | 29 ++- vectorizing/solvers/color/ColorSolver.py | 58 +++++- vectorizing/solvers/color/legacy.py | 117 +++++++++++ vectorizing/svg/markup.py | 37 ++++ vectorizing/tests/color_reference.py | 42 ++++ vectorizing/tests/test_api_contracts.py | 33 ++++ vectorizing/tests/test_color_background.py | 12 +- .../tests/test_color_configurations.py | 181 ++++++++++++++++++ vectorizing/tests/test_color_equivalence.py | 4 +- vectorizing/tests/test_color_layer_artwork.py | 9 +- .../tests/test_color_layer_ownership.py | 1 + vectorizing/tests/test_color_layers.py | 1 + vectorizing/tests/test_color_p3.py | 25 ++- vectorizing/tests/test_developer_tools.py | 105 +++++++++- 19 files changed, 746 insertions(+), 53 deletions(-) create mode 100644 vectorizing/solvers/color/legacy.py create mode 100644 vectorizing/tests/test_color_configurations.py diff --git a/AGENTS.md b/AGENTS.md index 5b999a6..6e0edcb 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -8,7 +8,8 @@ to S3. Start with `README.md` for setup and usage. - `vectorizing/__init__.py`: app factory, request validation, cropping and API responses. - `vectorizing/solvers/binary/`: binary masks and tracing. -- `vectorizing/solvers/color/`: quantization, cluster cleanup, ordered masks and tracing. +- `vectorizing/solvers/color/`: original and experimental quantization, cluster cleanup, + ordered masks and tracing; `ColorSolver.py` defines named color configurations. - `vectorizing/geometry/` and `vectorizing/svg/`: path conversion, bounds and SVG serialization. - `vectorizing/util/`: image loading, color-mode normalization and size limits. - `vectorizing/server/`: environment settings, S3, logging and timing. @@ -48,14 +49,22 @@ docker compose --profile testing run --build --rm test \ - Keep smooth anti-aliasing and transparent exteriors. Do not hide seams with SVG strokes or `shape-rendering="crispEdges"`, or reduce normal tracing quality. -- Color masks use bounded overlaps, not full underpainting. The current rim is - two processed-image pixels; zoom enlarges it and very thin features may remain - covered. Do not promise universally exact holes and seam-free rendering. -- Preserve palette/centroid ordering, dtypes and overflow behavior, connectivity, - and independent mask storage when optimizing arrays. Rim conversion runs forward - because the next mask must still be cumulative. +- Color requests default to `configuration: "current"` (original quantization, + layer clipping and SVG formatting). POST JSON may select `"experimental"` for the + newer quantization, bounded two-pixel rims, opaque-background detection/isolation + and compact SVG formatting. Both profiles share bitmap creation. Keep binary + output unaffected by color configuration changes. +- Experimental color masks use bounded overlaps, not full underpainting. Zoom + enlarges the two-processed-pixel rim, and very thin features may remain covered. + Do not promise universally exact holes and seam-free rendering. +- Preserve each profile's palette/centroid ordering, dtypes and overflow behavior, + connectivity, and independent mask storage when optimizing arrays. Original + cleanup streams one color at a time to avoid retaining component grids for all + colors; compare it with the independent pairwise reference when changing it. + Experimental rim conversion runs forward because the next mask must still be + cumulative. - Preserve public defaults, response/error shapes, return containers, SVG paint - order and numeric formatting during refactors or performance work. + order and each profile's numeric formatting during refactors or performance work. - Image readers currently wrap all loading failures, including interrupts, and URL downloads have no timeout. These are tested legacy contracts, not recommendations; change them deliberately with updated tests, never incidentally during lint cleanup. @@ -69,7 +78,9 @@ docker compose --profile testing run --build --rm test \ **not** prove equivalence; do not delete or replace baselines just to make tests pass. - For output-preserving changes, capture before editing (or use a trusted baseline checkout), then compare SVG bytes, RGBA pixels, palettes, dimensions and bounds - with `scripts/vectorization_outputs.py`. See the README for commands. + with `scripts/vectorization_outputs.py`. Its default capture exercises `current`; + pass `--configuration experimental` to capture or benchmark the newer pipeline. + Benchmarks can select a separate `--baseline-configuration`. See the README. - For layer/geometry changes, check layer deletion, zero alpha and half opacity, transparent backgrounds and thin features, including `aftermath.png`. An assembled render alone cannot establish editability. diff --git a/README.md b/README.md index 3b500ad..efa95ea 100644 --- a/README.md +++ b/README.md @@ -65,6 +65,8 @@ Capture each version into a different directory, then compare: python scripts/vectorization_outputs.py capture .user/before --source-root /path/to/baseline python scripts/vectorization_outputs.py capture .user/after python scripts/vectorization_outputs.py compare .user/before .user/after +python scripts/vectorization_outputs.py capture .user/experimental --configuration experimental +python scripts/vectorization_outputs.py compare .user/before .user/experimental # for a newer-pipeline baseline python scripts/benchmark_vectorization.py --output .user/benchmark.json --case aftermath-16 ``` @@ -73,6 +75,7 @@ python scripts/benchmark_vectorization.py --output .user/benchmark.json --case a - Benchmark timing covers the solver, SVG serialization and bounds, not file decoding, HTTP/S3 or rasterization. Each sample uses a fresh process; peak RSS includes imports, input preparation, warmups and output checks. Linux and macOS memory units are normalized to MiB. - Add `--baseline-root /path/to/baseline` to benchmark two trusted checkouts in alternating order, with exact-output checks. `--repeats` defaults to 3 and `--warmups` to 1 per process. Output mismatches exit `1` but still save the report; timings have no pass/fail threshold. - Reports include runtime/source fingerprints and raw samples. `--label` can record commit IDs. Checkouts share the installed dependencies; this is not a dependency-isolated or production/concurrency benchmark. Use only trusted source roots. +- Captures and benchmarks use the source checkout's default color configuration unless `--configuration experimental` is passed. To compare the newer pipeline with a checkout from before configurations existed, pass `--configuration experimental` for the candidate and leave the baseline unconfigured. For two configured checkouts, `--baseline-configuration experimental` selects the baseline independently; unknown configurations fail rather than silently using a default. Binary cases ignore color configuration. Use the same `--case` selections for both captures, particularly when an older checkout lacks newer fixtures. For Docker, build the current scripts and mount only the output directory: @@ -96,6 +99,7 @@ The request format is the following: url: string, // Image URL solver: number, // Solver. 0 -> Binary, 1 -> Color color_count: number, // Number of colors (if applicable) + configuration: string, // Optional color profile: "current" (default) or "experimental" raw: boolean // If true, plain return plain SVG markup } ``` @@ -123,7 +127,9 @@ A typical response would be Or, if `raw = true` was supplied, just plain SVG markup -Color processing uses a gentle 3-pixel bilateral filter and removes only connected +Color processing can be selected per request with the optional `configuration` JSON field. The default `current` profile uses the original color quantization and layer clipping behavior. Set `configuration` to `experimental` to use the newer quantization, overlap-based layers, and opaque-background detection/isolation. The profiles are assembled from independently switchable solver stages, so behavior can be compared without removing either implementation. Unknown profile names are rejected with `INVALID_PARAMETERS`. + +The `experimental` profile's color processing uses a gentle 3-pixel bilateral filter and removes only connected components smaller than eight processed-image pixels, rather than rejecting thin regions based on their shape. Transparent pixels are protected; on opaque images, the most common surviving perimeter color is also protected to retain small @@ -138,15 +144,14 @@ constrains any outlying curve control points to the canvas. It keeps smooth edit vectors instead of failing the request, but can adjust curves near the canvas and round corners inward, reducing edge coverage on the affected layer. -SVGs use compact absolute/relative commands on an integer hundredth-pixel grid, -inside a `scale(.01)` group. This preserves the previous two-decimal coordinate -rounding, viewport, paint order and opacity without raster images or SVG strokes. -Binary tracing is unchanged, but both solvers use the compact serializer. Equivalent -geometry can produce small renderer-specific antialiasing differences; exact pixel -identity across viewers and zoom levels is not guaranteed. Potrace and pypotrace -remain dependencies under their existing GPL licenses. +The default color profile uses the original two-decimal SVG serialization. +Binary and `experimental` color responses use compact absolute/relative commands +on an integer hundredth-pixel grid inside a `scale(.01)` group. All profiles emit +editable vectors without raster images or strokes. Equivalent geometry can produce +small renderer-specific antialiasing differences across viewers and zoom levels. +Potrace and pypotrace remain dependencies under their existing GPL licenses. -Color layers have cutouts with a small overlap along shared edges to hide seams. +The `experimental` color layers have cutouts with a small overlap along shared edges to hide seams. The overlap is two pixels in the resized image before tracing, not screen pixels. Hiding a color can expose this rim; very thin features may remain covered, and zooming in makes the rim larger. No SVG strokes are added. diff --git a/scripts/_vectorization.py b/scripts/_vectorization.py index cd8941b..cedb524 100644 --- a/scripts/_vectorization.py +++ b/scripts/_vectorization.py @@ -82,6 +82,7 @@ def environment() -> dict[str, object]: def prepare_case( name: str, source_root: Path, + configuration: str | None = None, ) -> Callable[[], tuple[str, dict[str, object]]]: """Load a fixture once and return a fresh solver/SVG/bounds run for its checkout.""" source_root = source_root.resolve() @@ -100,7 +101,7 @@ def prepare_case( from vectorizing.server.timer import Timer from vectorizing.solvers.binary.BinarySolver import BinarySolver from vectorizing.solvers.color.ColorSolver import ColorSolver - from vectorizing.svg.markup import generate_SVG_markup + from vectorizing.svg import markup from vectorizing.util.read import convert_RGB_A if Path(vectorizing.__file__).resolve().parent != source_root / "vectorizing": @@ -108,6 +109,18 @@ def prepare_case( "A different checkout is already imported; use a fresh process", ) filename, solver, count = CASES[name] + solver_module = sys.modules[ColorSolver.__module__] + profiles = getattr(solver_module, "CONFIGURATIONS", {}) + selected = ( + configuration + if configuration is not None + else getattr(solver_module, "DEFAULT_CONFIGURATION", None) + ) + if configuration is not None and selected not in profiles: + raise ValueError( + f"Configuration {configuration!r} is not supported by {source_root}", + ) + color_args = (configuration,) if configuration is not None else () path = source_root / "vectorizing" / "tests" / "images" / filename with Image.open(path) as source: image = convert_RGB_A(source).copy() @@ -122,7 +135,7 @@ def run() -> tuple[str, dict[str, object]]: result = ( BinarySolver(image).solve() if solver == "binary" - else ColorSolver(image, count, Timer()).solve() + else ColorSolver(image, count, Timer(), *color_args).solve() ) paths, colors, width, height = result bounds = compound_paths_bounds(paths) @@ -132,7 +145,14 @@ def run() -> tuple[str, dict[str, object]]: for key, value in bounds.items() } palette = np.asarray(colors) - return generate_SVG_markup(*result), { + serialize = ( + markup.generate_original_SVG_markup + if solver == "color" + and selected in profiles + and profiles[selected].original_svg_serialization + else markup.generate_SVG_markup + ) + return serialize(*result), { "input": source_info, "colors": palette.tolist(), "colors_dtype": str(palette.dtype), diff --git a/scripts/benchmark_vectorization.py b/scripts/benchmark_vectorization.py index 00fdd06..7de73bd 100644 --- a/scripts/benchmark_vectorization.py +++ b/scripts/benchmark_vectorization.py @@ -20,7 +20,12 @@ def peak_rss_mib() -> float: return value / (1024 * 1024 if sys.platform == "darwin" else 1024) -def sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: +def sample( + name: str, + source_root: Path, + warmups: int, + configuration: str | None = None, +) -> dict[str, object]: """Warm one case, time one run and verify stable output in this fresh process.""" from scripts._vectorization import ( environment, @@ -29,7 +34,7 @@ def sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: source_hash, ) - run = prepare_case(name, source_root) + run = prepare_case(name, source_root, configuration) revision = source_hash(source_root) expected = None consistent = True @@ -53,7 +58,12 @@ def sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: } -def run_sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: +def run_sample( + name: str, + source_root: Path, + warmups: int, + configuration: str | None = None, +) -> dict[str, object]: """Run this script in a new interpreter, propagating worker failures.""" command = [ sys.executable, @@ -66,6 +76,8 @@ def run_sample(name: str, source_root: Path, warmups: int) -> dict[str, object]: "--warmups", str(warmups), ] + if configuration is not None: + command.extend(["--configuration", configuration]) # The executable and script are fixed; arguments are passed without a shell. result = subprocess.run(command, capture_output=True, text=True) # noqa: S603 if result.returncode: @@ -80,6 +92,7 @@ def benchmark( roots: dict[str, Path], repeats: int, warmups: int, + configurations: dict[str, str | None] | None = None, ) -> tuple[dict[str, object], bool]: """Alternate variants, retaining raw samples and exact-output equality checks.""" cases = {} @@ -89,7 +102,14 @@ def benchmark( for iteration in range(repeats): order = list(roots) if iteration % 2 == 0 else list(reversed(roots)) for variant in order: - samples[variant].append(run_sample(name, roots[variant], warmups)) + samples[variant].append( + run_sample( + name, + roots[variant], + warmups, + (configurations or {}).get(variant), + ), + ) reference = next(iter(samples.values()))[0]["output"] equal = all( row["consistent"] and row["output"] == reference @@ -157,6 +177,14 @@ def main(argv: list[str] | None = None) -> int: choices=CASES, help="Repeat to select cases; default: all", ) + parser.add_argument( + "--configuration", + help="Candidate color profile; omitted uses its default", + ) + parser.add_argument( + "--baseline-configuration", + help="Baseline color profile; omitted uses its checkout's default", + ) parser.add_argument("--repeats", type=positive, default=3) parser.add_argument( "--warmups", @@ -177,22 +205,40 @@ def main(argv: list[str] | None = None) -> int: raise ValueError("A worker measures exactly one case") print( json.dumps( - sample(names[0], args.source_root, args.warmups), + sample( + names[0], + args.source_root, + args.warmups, + args.configuration, + ), allow_nan=False, ), ) return 0 if args.output is None: raise ValueError("--output is required") + if args.baseline_configuration is not None and args.baseline_root is None: + raise ValueError("--baseline-configuration requires --baseline-root") if args.output.exists(): raise ValueError(f"Refusing to overwrite: {args.output}") roots = {"baseline": args.baseline_root.resolve()} if args.baseline_root else {} roots["candidate"] = args.source_root.resolve() - cases, equal = benchmark(names, roots, args.repeats, args.warmups) + configurations = { + "baseline": args.baseline_configuration, + "candidate": args.configuration, + } + cases, equal = benchmark( + names, + roots, + args.repeats, + args.warmups, + configurations, + ) report = { "schema_version": 1, "label": args.label, "source_roots": {name: str(path) for name, path in roots.items()}, + "configurations": {name: configurations[name] for name in roots}, "repeats": args.repeats, "warmups_per_process": args.warmups, "timing_scope": "solver, SVG serialization, colors, dimensions and bounds", diff --git a/scripts/vectorization_outputs.py b/scripts/vectorization_outputs.py index 1b86e0d..74e7767 100644 --- a/scripts/vectorization_outputs.py +++ b/scripts/vectorization_outputs.py @@ -12,6 +12,7 @@ def capture( names: list[str], source_root: Path, label: str | None, + configuration: str | None = None, ) -> None: """Write a complete manifest last, refusing to replace existing artifacts.""" from cairosvg import svg2png @@ -28,7 +29,7 @@ def capture( output.mkdir(parents=True, exist_ok=True) cases = {} for name in names: - svg, details = prepare_case(name, source_root)() + svg, details = prepare_case(name, source_root, configuration)() svg_bytes = svg.encode("utf-8") for extension, data in { "svg": svg_bytes, @@ -46,6 +47,7 @@ def capture( report = { "schema_version": 1, "label": label, + "configuration": configuration, "source_root": str(source_root.resolve()), "source_sha256": source_hash(source_root), "environment": environment(), @@ -155,6 +157,10 @@ def main(argv: list[str] | None = None) -> int: "--label", help="Optional revision or description for the manifest", ) + save.add_argument( + "--configuration", + help="Color profile in the source checkout; omitted uses its default", + ) diff = commands.add_parser( "compare", help="Compare complete captures; exit 1 on changes", @@ -170,6 +176,7 @@ def main(argv: list[str] | None = None) -> int: list(dict.fromkeys(args.case or CASES)), args.source_root, args.label, + args.configuration, ) return 0 except (OSError, ValueError, ImportError) as error: diff --git a/vectorizing/__init__.py b/vectorizing/__init__.py index 26d04e5..1195a05 100644 --- a/vectorizing/__init__.py +++ b/vectorizing/__init__.py @@ -16,8 +16,12 @@ from vectorizing.server.s3 import upload_markup from vectorizing.server.timer import Timer from vectorizing.solvers.binary.BinarySolver import BinarySolver -from vectorizing.solvers.color.ColorSolver import ColorSolver -from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.solvers.color.ColorSolver import ( + CONFIGURATIONS, + DEFAULT_CONFIGURATION, + ColorSolver, +) +from vectorizing.svg.markup import generate_original_SVG_markup, generate_SVG_markup from vectorizing.util.read import try_read_image_from_url # 0 -> BinarySolver @@ -46,9 +50,10 @@ def process_color( img: Image.Image, color_count: int | None, timer: Timer, + configuration: str = DEFAULT_CONFIGURATION, ) -> list[list[Path] | list[np.ndarray] | int]: - """Trace color layers with bounded overlaps and return processed dimensions.""" - solver = ColorSolver(img, color_count, timer) + """Trace color layers using a named processing configuration.""" + solver = ColorSolver(img, color_count, timer, configuration) return solver.solve() @@ -61,6 +66,10 @@ def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: if solver not in SOLVERS: return False + configuration = args.get("configuration", DEFAULT_CONFIGURATION) + if not isinstance(configuration, str) or configuration not in CONFIGURATIONS: + return False + box = args.get("crop_box") if box: if len(box) != 4: @@ -76,6 +85,7 @@ def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: url=args.get("url"), raw=args.get("raw"), color_count=args.get("color_count"), + configuration=configuration, ) @@ -100,6 +110,7 @@ def index() -> str | Response | tuple[Response, int]: url = args.url solver = args.solver color_count = args.color_count + configuration = args.configuration raw = args.raw crop_box = args.crop_box @@ -120,13 +131,19 @@ def index() -> str | Response | tuple[Response, int]: else: timer.start_timer("Color Solver - Total") - solved = process_color(img, color_count, timer) + solved = process_color(img, color_count, timer, configuration) timer.end_timer() compound_paths, colors, width, height = solved timer.start_timer("Markup Creation") - markup = generate_SVG_markup(compound_paths, colors, width, height) + serialize = ( + generate_original_SVG_markup + if solver == 1 + and CONFIGURATIONS[configuration].original_svg_serialization + else generate_SVG_markup + ) + markup = serialize(compound_paths, colors, width, height) timer.end_timer() if raw: diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index c91a015..b2920d9 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -1,6 +1,7 @@ """Trace editable color layers with bounded overlap at shared edges.""" import logging +from dataclasses import dataclass import numpy as np import potrace @@ -9,6 +10,7 @@ from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.server.timer import Timer +from vectorizing.solvers.color import legacy from vectorizing.solvers.color.bitmaps import ( add_bitmap_rims, create_background_bitmap, @@ -18,6 +20,28 @@ from vectorizing.util.limit_size import limit_size +@dataclass(frozen=True) +class ColorConfiguration: + """Switchable color-processing stages collected into named presets.""" + + original_quantization: bool = False + original_layer_clipping: bool = False + detect_opaque_background: bool = True + original_svg_serialization: bool = False + + +CONFIGURATIONS = { + "current": ColorConfiguration( + original_quantization=True, + original_layer_clipping=True, + detect_opaque_background=False, + original_svg_serialization=True, + ), + "experimental": ColorConfiguration(), +} +DEFAULT_CONFIGURATION = "current" + + def _trace_mask(bitmap: np.ndarray) -> Path: """Trace a mask with the same detail settings on normal and recovery paths.""" traced = potrace.Bitmap(bitmap).trace(turdsize=0, opttolerance=0.5, alphamax=1) @@ -70,7 +94,13 @@ def trace_bitmap(bitmap: np.ndarray, *, recover_clip: bool = True) -> Path: class ColorSolver: """Resize and quantize an image, then trace its ordered color layers.""" - def __init__(self, img: Image.Image, color_count: int | None, timer: Timer) -> None: + def __init__( + self, + img: Image.Image, + color_count: int | None, + timer: Timer, + configuration: str = DEFAULT_CONFIGURATION, + ) -> None: color_count = color_count or ColorSolver.DEFAULT_COLOR_COUNT color_count = max(color_count, ColorSolver.MIN_COLOR_COUNT) color_count = min(color_count, ColorSolver.MAX_COLOR_COUNT) @@ -82,21 +112,39 @@ def __init__(self, img: Image.Image, color_count: int | None, timer: Timer) -> N self.img_arr = np.asarray(self.img).astype(np.uint8) self.timer = timer + self.configuration = CONFIGURATIONS[configuration] def solve(self) -> list[list[Path] | list[np.ndarray] | int]: """Return paths, colors, width and height as a list.""" self.timer.start_timer("Quantization") - labels, colors, has_background = quantize(self.img_arr, self.color_count) + quantizer = ( + legacy.quantize if self.configuration.original_quantization else quantize + ) + labels, colors, has_background = quantizer(self.img_arr, self.color_count) self.timer.end_timer() self.timer.start_timer("Bitmap Creation") - background_bitmap = create_background_bitmap(labels, colors, has_background) + background_bitmap = ( + create_background_bitmap(labels, colors, has_background) + if self.configuration.detect_opaque_background + else None + ) bitmaps, colors = create_bitmaps(labels, colors, has_background) - add_bitmap_rims(bitmaps) + if not self.configuration.original_layer_clipping: + add_bitmap_rims(bitmaps) self.timer.end_timer() self.timer.start_timer("Bitmap Tracing") - compound_paths = [trace_bitmap(bitmap) for bitmap in bitmaps] + if self.configuration.original_layer_clipping: + traced = [potrace.Bitmap(bitmap).trace() for bitmap in bitmaps] + compound_paths = legacy.remove_layering( + traced, + self.img.size[0], + self.img.size[1], + has_background, + ) + else: + compound_paths = [trace_bitmap(bitmap) for bitmap in bitmaps] if background_bitmap is not None: try: background = trace_bitmap(background_bitmap, recover_clip=False) diff --git a/vectorizing/solvers/color/legacy.py b/vectorizing/solvers/color/legacy.py new file mode 100644 index 0000000..0abea64 --- /dev/null +++ b/vectorizing/solvers/color/legacy.py @@ -0,0 +1,117 @@ +"""Color-processing operations retained for the pre-layer-seam configuration.""" + +import cv2 +import numpy as np +import potrace +import scipy.ndimage as ndi +from pathops import Path, PathOp, op +from skimage.measure import label + +from vectorizing.geometry.potrace import potrace_path_to_compound_path +from vectorizing.solvers.color.quantize import ( + get_background_cluster, + get_initial_centroids, + kmeans, +) + + +def quantize( + img_arr: np.ndarray, + color_count: int, +) -> tuple[np.ndarray, np.ndarray, bool]: + """Run the original strong-filter and overlap-based component cleanup.""" + background = get_background_cluster(img_arr) if img_arr.shape[-1] == 4 else None + rgb = ( + cv2.cvtColor(img_arr, cv2.COLOR_RGBA2RGB) if img_arr.shape[-1] == 4 else img_arr + ) + rgb = cv2.bilateralFilter(rgb.copy(), 7, 50, 50) + labels, colors = kmeans(rgb, get_initial_centroids(rgb, color_count)) + labels = labels.reshape(rgb.shape[:2]) + if background is not None: + labels = np.where(background > 0, 0, labels + 1) + colors = np.vstack( + ( + np.zeros((1, 4), dtype=np.uint8), + np.column_stack((colors, np.ones(len(colors), dtype=np.uint8))), + ), + ) + labels = labels + 1 + enhanced = np.zeros(labels.shape, dtype=np.uint16) + kernel = np.ones((2, 2)) + for index in range(len(colors)): + mask = labels == index + 1 + if not mask.any(): + continue + components = label(mask) + 1 + counts = np.bincount(components.ravel()) + # A pixel is erased from this component when any other color's + # two-pixel dilation covers it. The union replaces pairwise overlaps. + covered = cv2.dilate((~mask).astype(np.uint8), kernel) > 0 + remaining = np.bincount(components[mask & ~covered], minlength=len(counts)) + ratio = np.divide( + remaining.astype(np.float32), + counts.astype(np.float32), + out=np.ones(len(counts), dtype=np.float32), + where=counts != 0, + ) + enhanced[mask & (ratio[components] > 0.1)] = index + 1 + nearest = ndi.distance_transform_edt( + enhanced == 0, + return_distances=False, + return_indices=True, + ) + enhanced = np.where(enhanced != 0, enhanced, enhanced[tuple(nearest)]) + return enhanced - 1, colors.astype(np.uint8), background is not None + + +def create_background_rect(width: int, height: int, padding: int) -> Path: + """Build the padded clipping rectangle used by the original layer solver.""" + rect = Path() + rect.moveTo(-padding, -padding) + rect.lineTo(width + padding, -padding) + rect.lineTo(width + padding, height + padding) + rect.lineTo(-padding, height + padding) + rect.close() + return rect + + +def remove_layering( + traced_bitmaps: list[potrace.Path], + width: int, + height: int, + has_background: bool, +) -> list[Path]: + """Apply the original boolean clipping strategy to traced palette layers.""" + paths = [potrace_path_to_compound_path(path) for path in traced_bitmaps] + if has_background: + for i in range(len(paths) - 1): + try: + paths[i] = op(paths[i], paths[i + 1], PathOp.DIFFERENCE) + except Exception: + break + return paths + + disjoint = [] + for i in range(len(paths) - 1): + subtract = Path() + for path in disjoint: + subtract.addPath(path) + subtract.addPath(paths[i + 1]) + try: + disjoint.append( + op( + create_background_rect(width, height, (i + 1) * 10), + subtract, + PathOp.DIFFERENCE, + ), + ) + except Exception: + break + try: + disjoint = [ + op(path, create_background_rect(width, height, 0), PathOp.INTERSECTION) + for path in disjoint + ] + except Exception: + return paths + return disjoint + paths[len(disjoint) :] diff --git a/vectorizing/svg/markup.py b/vectorizing/svg/markup.py index 9dfb8a9..3030af3 100644 --- a/vectorizing/svg/markup.py +++ b/vectorizing/svg/markup.py @@ -112,6 +112,43 @@ def _path_data(path: Path, width: int, height: int) -> str: return "".join(pieces) +def generate_original_SVG_markup( + compound_paths: Iterable[Path], + colors: Iterable[Sequence[float] | np.ndarray], + width: int, + height: int, +) -> str: + """Serialize with the original absolute commands and two-decimal coordinates.""" + paths_markup = [] + for compound_path, color in zip(compound_paths, colors): + segments = list(compound_path.segments) + if not segments: + continue + data = "" + for command, points in segments: + if command == "moveTo": + data += f"M {truncate(points[0][0])} {truncate(points[0][1])} " + if command == "lineTo": + data += f"L {truncate(points[0][0])} {truncate(points[0][1])} " + if command == "curveTo": + data += ( + "C" + f"{truncate(points[0][0])},{truncate(points[0][1])} " + f"{truncate(points[1][0])},{truncate(points[1][1])} " + f"{truncate(points[2][0])},{truncate(points[2][1])} " + ) + if command == "closePath": + data += "Z" + paths_markup.append( + f'', + ) + markup = "\n".join(paths_markup) + return ( + f'\n' + f"\n{markup}\n\n" + ) + + def generate_SVG_markup( compound_paths: Iterable[Path], colors: Iterable[Sequence[float] | np.ndarray], diff --git a/vectorizing/tests/color_reference.py b/vectorizing/tests/color_reference.py index 2b93675..c868dac 100644 --- a/vectorizing/tests/color_reference.py +++ b/vectorizing/tests/color_reference.py @@ -5,6 +5,8 @@ import cv2 import numpy as np from PIL import Image +from scipy.ndimage import distance_transform_edt +from skimage.measure import label def legacy_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: @@ -43,6 +45,46 @@ def legacy_create_bitmaps( return bitmaps, colors +def original_area_cleanup(labels: np.ndarray, color_count: int) -> np.ndarray: + """Run the original pairwise-dilation component cleanup on a small label grid.""" + shifted = labels + 1 + clusters = [ + np.where(shifted == index + 1, index + 1, 0).astype(np.uint16) + for index in range(color_count) + ] + original = [label(cluster) + 1 for cluster in clusters] + counts = [np.bincount(components.ravel()) for components in original] + remaining = [components.copy() for components in original] + for x, cluster_x in enumerate(clusters): + dilated = cv2.dilate(cluster_x, np.ones((2, 2))) + for y, cluster_y in enumerate(clusters): + if x != y: + remaining[y] = np.where( + np.logical_and(dilated, cluster_y), + 0, + remaining[y], + ) + for x, components in enumerate(remaining): + current = np.bincount(components.ravel(), minlength=len(counts[x])) + ratio = np.divide( + current.astype(np.float32), + counts[x].astype(np.float32), + out=np.ones(len(counts[x]), dtype=np.float32), + where=counts[x] != 0, + ) + clusters[x] = np.where(ratio[original[x]] <= 0.1, 0, clusters[x]) + enhanced = np.zeros(labels.shape, dtype=np.uint8) + for cluster in clusters: + enhanced = np.where(enhanced == 0, cluster, enhanced) + nearest = distance_transform_edt( + enhanced == 0, + return_distances=False, + return_indices=True, + ) + enhanced = np.where(enhanced != 0, enhanced, enhanced[tuple(nearest)]) + return enhanced - 1 + + def reference_clean_components( labels: np.ndarray, background: np.ndarray | None, diff --git a/vectorizing/tests/test_api_contracts.py b/vectorizing/tests/test_api_contracts.py index c46236a..6c28e81 100644 --- a/vectorizing/tests/test_api_contracts.py +++ b/vectorizing/tests/test_api_contracts.py @@ -19,6 +19,10 @@ {"url": "image", "solver": "1"}, {"url": "image", "crop_box": [0, 0, 3]}, {"url": "image", "crop_box": [0, 0, 3.5, 4]}, + {"url": "image", "configuration": "unknown"}, + {"url": "image", "configuration": "legacy"}, + {"url": "image", "configuration": None}, + {"url": "image", "configuration": []}, ], ) def test_invalid_arguments_return_the_same_error( @@ -36,6 +40,7 @@ def test_invalid_arguments_return_the_same_error( "payload", [ {"url": "image"}, + {"url": "image", "configuration": "experimental"}, {"url": None}, {"url": "image", "solver": True}, {"url": "image", "crop_box": []}, @@ -54,6 +59,7 @@ def test_argument_validation_preserves_accepted_values( "crop_box": payload.get("crop_box"), "raw": None, "color_count": None, + "configuration": payload.get("configuration", "current"), } @@ -89,12 +95,39 @@ def test_raw_requests_crop_before_vectorizing_and_do_not_upload( assert b'width="8" height="8"' in response.data chosen, unused = (binary, color) if solver == 0 else (color, binary) chosen.assert_called_once() + if solver == 1: + assert chosen.call_args.args[3] == "current" assert chosen.call_args.args[0].size == (4, 4) unused.assert_not_called() load.assert_called_once_with("image") upload.assert_not_called() +def test_color_configuration_can_be_forced( + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Pass a named request configuration through to color processing.""" + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(return_value=Image.new("RGB", (8, 8))), + ) + color = Mock(return_value=([], [], 8, 8)) + monkeypatch.setattr(vectorizing, "process_color", color) + response = client.post( + "/", + json={ + "url": "image", + "solver": 1, + "configuration": "experimental", + "raw": True, + }, + ) + assert response.status_code == 200 + assert color.call_args.args[3] == "experimental" + + def test_processing_failure_keeps_json_error( client: FlaskClient, monkeypatch: pytest.MonkeyPatch, diff --git a/vectorizing/tests/test_color_background.py b/vectorizing/tests/test_color_background.py index 9209bfa..363cb24 100644 --- a/vectorizing/tests/test_color_background.py +++ b/vectorizing/tests/test_color_background.py @@ -129,7 +129,7 @@ def test_partial_alpha_uses_existing_transparency_classification( labels, palette = background_labels rgba = np.dstack([palette[labels], np.full(labels.shape, 255, np.uint8)]) rgba[0, 0, 3] = 217 - result = ColorSolver(Image.fromarray(rgba), 3, Timer()).solve() + result = ColorSolver(Image.fromarray(rgba), 3, Timer(), "experimental").solve() assert isinstance(result, list) np.testing.assert_array_equal(result[1][0], palette[2]) @@ -181,7 +181,15 @@ def controlled_op(*args: object, **kwargs: object) -> object: monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.op", controlled_op) upload = Mock(return_value="original-layers") monkeypatch.setattr("vectorizing.upload_markup", upload) - response = client.post("/", json={"url": "unused", "solver": 1, "raw": raw}) + response = client.post( + "/", + json={ + "url": "unused", + "solver": 1, + "configuration": "experimental", + "raw": raw, + }, + ) assert response.status_code == 200 if raw: markup = response.data.decode() diff --git a/vectorizing/tests/test_color_configurations.py b/vectorizing/tests/test_color_configurations.py new file mode 100644 index 0000000..f90e078 --- /dev/null +++ b/vectorizing/tests/test_color_configurations.py @@ -0,0 +1,181 @@ +"""Keep both selectable color pipelines covered by their independent outputs.""" + +import hashlib +import tracemalloc +from pathlib import Path +from unittest.mock import Mock + +import numpy as np +import pytest +from flask.testing import FlaskClient +from PIL import Image + +import vectorizing +from vectorizing.server.timer import Timer +from vectorizing.solvers.color import legacy +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_SVG_markup +from vectorizing.tests.color_reference import original_area_cleanup +from vectorizing.util.limit_size import limit_size +from vectorizing.util.read import convert_RGB_A + + +def transparent_artwork() -> Image.Image: + """Build opaque nested colors with transparent exterior and an alpha hole.""" + pixels = np.zeros((36, 36, 4), dtype=np.uint8) + pixels[:] = [30, 100, 220, 0] + pixels[3:33, 3:33] = [240, 230, 190, 255] + pixels[9:27, 9:27] = [35, 60, 130, 255] + pixels[16:20, 16:20] = [220, 10, 40, 255] + pixels[13:15, 13:15, 3] = 0 + return Image.fromarray(pixels) + + +def test_default_quantization_matches_original_rgba_output() -> None: + """Pin the original palette, transparent cluster, label dtype and mask bytes.""" + labels, colors, has_background = legacy.quantize( + np.asarray(transparent_artwork()), + 4, + ) + assert has_background + assert labels.dtype == np.uint16 + assert hashlib.sha256(labels.tobytes()).hexdigest() == ( + "e410dd6134fe3fe03bf99b184f1dd4f0bf5a03d007d3c42b6b36e6bd8f9bc226" + ) + np.testing.assert_array_equal( + colors, + [ + [0, 0, 0, 0], + [30, 100, 220, 1], + [35, 59, 130, 1], + [220, 10, 40, 1], + [240, 230, 190, 1], + ], + ) + + +def test_original_rgb_component_cleanup_matches_reference() -> None: + """Check the original connected-component decisions, including tiny clusters.""" + path = Path(__file__).parent / "images" / "shapes_2.png" + with Image.open(path) as image: + labels, colors, has_background = legacy.quantize( + np.asarray(limit_size(image.convert("RGB"))).astype(np.uint8), + 7, + ) + assert not has_background + assert hashlib.sha256(labels.tobytes()).hexdigest() == ( + "a5455fcdb7c920fa369f9ab26304277bde52f3267d195712b1ecf4df132ab831" + ) + np.testing.assert_array_equal( + colors, + [ + [22, 22, 22], + [31, 172, 153], + [101, 205, 35], + [169, 20, 20], + [201, 20, 20], + [225, 21, 178], + [227, 230, 39], + ], + ) + + +@pytest.mark.parametrize("count", [2, 6, 16, 64]) +@pytest.mark.parametrize("transparent", [False, True]) +@pytest.mark.parametrize("seed", range(4)) +def test_original_cleanup_matches_pairwise_reference( + count: int, + transparent: bool, + seed: int, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Stream components without changing overlap ratios or filled labels.""" + rng = np.random.default_rng(seed) + assigned = rng.integers(0, count, (11, 13), dtype=np.uint8) + colors = rng.integers(0, 256, (count, 3), dtype=np.uint8) + image = np.zeros((11, 13, 4 if transparent else 3), dtype=np.uint8) + if transparent: + image[:, :, 3] = 255 + image[2:5, 3:6, 3] = 0 + original_labels = np.where(image[:, :, 3] == 0, 0, assigned + 1) + else: + original_labels = assigned + monkeypatch.setattr(legacy, "get_initial_centroids", lambda *_: colors) + monkeypatch.setattr(legacy, "kmeans", lambda *_: (assigned.reshape(-1, 1), colors)) + actual, palette, has_background = legacy.quantize(image, count) + np.testing.assert_array_equal( + actual, + original_area_cleanup(original_labels, count + int(transparent)), + ) + assert actual.dtype == np.uint16 + assert has_background is transparent + assert len(palette) == count + int(transparent) + + +def test_original_cleanup_keeps_working_memory_bounded( + monkeypatch: pytest.MonkeyPatch, +) -> None: + """A 64-color image must not retain a component grid per palette entry.""" + rng = np.random.default_rng(731) + assigned = rng.integers(0, 64, (256, 256), dtype=np.uint8) + colors = rng.integers(0, 256, (64, 3), dtype=np.uint8) + monkeypatch.setattr(legacy, "get_initial_centroids", lambda *_: colors) + monkeypatch.setattr(legacy, "kmeans", lambda *_: (assigned.reshape(-1, 1), colors)) + tracemalloc.start() + try: + legacy.quantize(np.zeros((256, 256, 3), dtype=np.uint8), 64) + _, peak = tracemalloc.get_traced_memory() + finally: + tracemalloc.stop() + assert peak < 32 * 1024 * 1024 + + +def test_original_opaque_svg_matches_reference( + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Pin the opaque API output captured from the original implementation.""" + path = Path(__file__).parent / "images" / "black_rectangle.png" + with Image.open(path) as source: + image = convert_RGB_A(source).copy() + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(return_value=image), + ) + response = client.post( + "/", + json={"url": "image", "solver": 1, "color_count": 5, "raw": True}, + ) + assert response.status_code == 200 + assert hashlib.sha256(response.data).hexdigest() == ( + "6cc923711ade26ecda686ded32401cee8d3d730c4adc9e5a5e85151089d4bea1" + ) + + +def test_original_profile_is_http_default_and_experimental_is_independent( + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Pin original raw SVG bytes while keeping the newer pipeline selectable.""" + image = transparent_artwork() + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(return_value=image), + ) + base = {"url": "image", "solver": 1, "color_count": 4, "raw": True} + default = client.post("/", json=base) + original = client.post("/", json={**base, "configuration": "current"}) + experimental = client.post("/", json={**base, "configuration": "experimental"}) + assert all(r.status_code == 200 for r in (default, original, experimental)) + assert default.data == original.data + # Captured from the pre-change solver and SVG serializer, not this implementation. + assert hashlib.sha256(default.data).hexdigest() == ( + "901127e424e2944c199af568da7bf136373b825a8f2939b1df109ed0c1269632" + ) + assert experimental.data != default.data + assert experimental.data.decode() == generate_SVG_markup( + *ColorSolver(image, 4, Timer(), "experimental").solve(), + ) + assert client.post("/", json=base).data == default.data diff --git a/vectorizing/tests/test_color_equivalence.py b/vectorizing/tests/test_color_equivalence.py index 99f9d8d..9a41405 100644 --- a/vectorizing/tests/test_color_equivalence.py +++ b/vectorizing/tests/test_color_equivalence.py @@ -40,7 +40,7 @@ def test_color_optimizations_preserve_vectorization( ) -> None: """Compare SVG, colors, dimensions and bounds with independent operation oracles.""" with Image.open(Path(__file__).parent / "images" / image_name) as image: - actual = ColorSolver(image, color_count, Timer()).solve() + actual = ColorSolver(image, color_count, Timer(), "experimental").solve() target, legacy = { "centroids": ( "vectorizing.solvers.color.quantize.get_initial_centroids", @@ -58,7 +58,7 @@ def test_color_optimizations_preserve_vectorization( # Patch each lookup site and verify the legacy implementation was used. reference = Mock(wraps=legacy) monkeypatch.setattr(target, reference) - expected = ColorSolver(image, color_count, Timer()).solve() + expected = ColorSolver(image, color_count, Timer(), "experimental").solve() reference.assert_called_once() actual_paths, actual_colors, actual_width, actual_height = actual diff --git a/vectorizing/tests/test_color_layer_artwork.py b/vectorizing/tests/test_color_layer_artwork.py index d30624f..133d189 100644 --- a/vectorizing/tests/test_color_layer_artwork.py +++ b/vectorizing/tests/test_color_layer_artwork.py @@ -20,7 +20,7 @@ def test_opaque_artwork_has_no_alpha_seams(filename: str, count: int) -> None: """Keep opaque artwork opaque through every shared boundary.""" with Image.open(Path(__file__).parent / "images" / filename) as image: - result = ColorSolver(image, count, Timer()).solve() + result = ColorSolver(image, count, Timer(), "experimental").solve() markup = generate_SVG_markup(*result) pixels = np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) np.testing.assert_array_equal(pixels[:, :, 3], 255) @@ -47,7 +47,12 @@ def capture_foreground(masks: list[np.ndarray]) -> None: rim_builder, ) with Image.open(Path(__file__).parent / "images" / "aftermath.png") as image: - paths, colors, width, height = ColorSolver(image, 16, Timer()).solve() + paths, colors, width, height = ColorSolver( + image, + 16, + Timer(), + "experimental", + ).solve() rim_builder.assert_called_once() markup = generate_SVG_markup(paths, colors, width, height) full = np.asarray(Image.open(BytesIO(svg2png(bytestring=markup))).convert("RGBA")) diff --git a/vectorizing/tests/test_color_layer_ownership.py b/vectorizing/tests/test_color_layer_ownership.py index d7e6080..52b316b 100644 --- a/vectorizing/tests/test_color_layer_ownership.py +++ b/vectorizing/tests/test_color_layer_ownership.py @@ -42,6 +42,7 @@ def customer_svg(request: pytest.FixtureRequest) -> tuple[str, tuple[int, ...]]: image, request.param, Timer(), + "experimental", ).solve() # On this fixture the cream background is the last RGB-ordered color, not # the first foreground color. It must become the first emitted layer. diff --git a/vectorizing/tests/test_color_layers.py b/vectorizing/tests/test_color_layers.py index c14bb05..c86e301 100644 --- a/vectorizing/tests/test_color_layers.py +++ b/vectorizing/tests/test_color_layers.py @@ -27,6 +27,7 @@ def trace_layers( Image.fromarray(palette[labels]), 3, Timer(), + "experimental", ).solve() quantize.assert_called_once() return paths, retained diff --git a/vectorizing/tests/test_color_p3.py b/vectorizing/tests/test_color_p3.py index 73e3dab..71e4a6d 100644 --- a/vectorizing/tests/test_color_p3.py +++ b/vectorizing/tests/test_color_p3.py @@ -40,7 +40,12 @@ def capture_rims(bitmaps: list[np.ndarray]) -> None: capture_rims, ) with Image.open(IMAGES / "aftermath.png") as image: - paths, colors, width, height = ColorSolver(image, 8, Timer()).solve() + paths, colors, width, height = ColorSolver( + image, + 8, + Timer(), + "experimental", + ).solve() # Ordered masks are identical across ARM64 and x86_64. Native Potrace makes # different curve-optimization decisions on those identical inputs. Both # geometry captures were checked for coverage and composited render error; @@ -79,7 +84,7 @@ def capture_rims(bitmaps: list[np.ndarray]) -> None: def bubbles_pixels() -> np.ndarray: """Render the real 16-color artwork at its original dimensions.""" with Image.open(IMAGES / "bubbles.png") as image: - result = ColorSolver(image, 16, Timer()).solve() + result = ColorSolver(image, 16, Timer(), "experimental").solve() png = svg2png( bytestring=generate_SVG_markup(*result), output_width=image.width, @@ -178,7 +183,15 @@ def test_clip_failure_retraces_bounded_vectors( monkeypatch.setattr("vectorizing.solvers.color.ColorSolver.op", clip) upload = Mock(return_value="fallback-svg") monkeypatch.setattr("vectorizing.upload_markup", upload) - response = client.post("/", json={"url": "unused", "solver": 1, "raw": raw}) + response = client.post( + "/", + json={ + "url": "unused", + "solver": 1, + "configuration": "experimental", + "raw": raw, + }, + ) assert response.status_code == 200 clip.assert_called_once() assert "retracing without padding" in caplog.text @@ -218,7 +231,7 @@ def test_clip_recovery_constrains_curve_overshoot( def test_clipped_logo_preserves_opaque_canvas() -> None: """Keep coverage on a real clipped logo, including the canvas boundary.""" with Image.open(IMAGES / "geo_logo.png") as image: - result = ColorSolver(image, 8, Timer()).solve() + result = ColorSolver(image, 8, Timer(), "experimental").solve() markup = generate_SVG_markup(*result) png = svg2png(bytestring=markup) pixels = np.asarray(Image.open(BytesIO(png)).convert("RGBA")) @@ -232,7 +245,7 @@ def test_clipped_consecutive_quadratics_keep_opaque_coverage() -> None: mask = rng.random((height, width)) < rng.uniform(0.03, 0.98) pixels = np.full((height, width, 3), 255, dtype=np.uint8) pixels[mask] = [255, 0, 0] - result = ColorSolver(Image.fromarray(pixels), 2, Timer()).solve() + result = ColorSolver(Image.fromarray(pixels), 2, Timer(), "experimental").solve() rendered = np.asarray( Image.open( BytesIO(svg2png(bytestring=generate_SVG_markup(*result))), @@ -248,5 +261,5 @@ def test_fully_transparent_image_has_no_foreground() -> None: assert background np.testing.assert_array_equal(labels, 0) assert palette.dtype == np.uint8 - result = ColorSolver(Image.fromarray(pixels), 16, Timer()).solve() + result = ColorSolver(Image.fromarray(pixels), 16, Timer(), "experimental").solve() assert result[0] == [] diff --git a/vectorizing/tests/test_developer_tools.py b/vectorizing/tests/test_developer_tools.py index 2df8f3a..40ce371 100644 --- a/vectorizing/tests/test_developer_tools.py +++ b/vectorizing/tests/test_developer_tools.py @@ -87,6 +87,49 @@ def test_changed_metadata_fails( assert outputs.main(["compare", str(before), str(after)]) == 1 +def test_capture_selects_both_color_profiles(tmp_path: Path) -> None: + """Profile selection changes real solver and SVG bytes, not only metadata.""" + default = tmp_path / "current" + explicit = tmp_path / "explicit-current" + experimental = tmp_path / "experimental" + options = ["--case", "black_rectangle_color"] + assert outputs.main(["capture", str(default), *options]) == 0 + assert ( + outputs.main(["capture", str(explicit), *options, "--configuration", "current"]) + == 0 + ) + assert outputs.main(["compare", str(default), str(explicit)]) == 0 + assert ( + outputs.main( + ["capture", str(experimental), *options, "--configuration", "experimental"], + ) + == 0 + ) + assert ( + json.loads((experimental / "outputs.json").read_text())["configuration"] + == "experimental" + ) + assert outputs.main(["compare", str(default), str(experimental)]) == 1 + + +@pytest.mark.parametrize("case", ["black_rectangle_color", "1px_binary"]) +def test_invalid_source_configuration_fails(tmp_path: Path, case: str) -> None: + """Unknown names cannot silently appear in reports, even for binary cases.""" + with pytest.raises(SystemExit) as error: + outputs.main( + [ + "capture", + str(tmp_path), + "--case", + case, + "--configuration", + "missing", + ], + ) + assert error.value.code == 2 + assert not (tmp_path / "outputs.json").exists() + + def test_changed_svg_fails(tmp_path: Path, fake_solver: None) -> None: """Different SVG bytes fail even when both versions render identically.""" before, after = tmp_path / "before", tmp_path / "after" @@ -225,7 +268,13 @@ def test_alternation_medians_and_equality(monkeypatch: pytest.MonkeyPatch) -> No order = [] times = {"baseline": iter([9, 1, 5]), "candidate": iter([3, 1, 2])} - def measure(name: str, root: Path, warmups: int) -> dict[str, object]: + def measure( + name: str, + root: Path, + warmups: int, + configuration: str | None, + ) -> dict[str, object]: + assert configuration is None order.append(root.name) assert name == "bubbles" and warmups == 2 return { @@ -263,7 +312,13 @@ def test_benchmark_mismatches_save_failing_report( ) -> None: """Cross-version changes and within-process nondeterminism both fail the command.""" - def measure(name: str, root: Path, warmups: int) -> dict[str, object]: + def measure( + name: str, + root: Path, + warmups: int, + configuration: str | None, + ) -> dict[str, object]: + assert configuration is None return { "elapsed_ms": 1, "peak_rss_mib": 2, @@ -291,6 +346,52 @@ def measure(name: str, root: Path, warmups: int) -> dict[str, object]: assert json.loads(path.read_text())["outputs_equal"] is False +def test_benchmark_selects_each_profile_independently(tmp_path: Path) -> None: + """Fresh workers use the selected baseline and candidate profiles.""" + report = tmp_path / "benchmark.json" + assert ( + bench.main( + [ + "--output", + str(report), + "--baseline-root", + str(shared.ROOT), + "--baseline-configuration", + "experimental", + "--configuration", + "experimental", + "--case", + "black_rectangle_color", + "--repeats", + "1", + "--warmups", + "0", + ], + ) + == 0 + ) + data = json.loads(report.read_text()) + assert data["configurations"] == { + "baseline": "experimental", + "candidate": "experimental", + } + assert data["outputs_equal"] + + +def test_baseline_configuration_requires_checkout(tmp_path: Path) -> None: + """Do not silently discard a requested baseline profile.""" + with pytest.raises(SystemExit) as error: + bench.main( + [ + "--output", + str(tmp_path / "report.json"), + "--baseline-configuration", + "experimental", + ], + ) + assert error.value.code == 2 + + def test_warmups_and_instability( fake_solver: None, monkeypatch: pytest.MonkeyPatch, From cc81a345f4d1b4d4bb3e914abea4770d5eb6d768 Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Tue, 29 Sep 2026 12:10:17 +0200 Subject: [PATCH 15/16] feat(color): select color count automatically (#88) * feat(color): auto-select palette size for artwork * fix(color): satisfy CI pre-commit hooks --- README.md | 6 +- vectorizing/__init__.py | 7 +- vectorizing/solvers/color/ColorSolver.py | 40 ++++- vectorizing/solvers/color/legacy.py | 10 +- vectorizing/solvers/color/quantize.py | 99 ++++++++++++- vectorizing/tests/images/test_logo.png | Bin 0 -> 867028 bytes vectorizing/tests/test_api_contracts.py | 27 +++- vectorizing/tests/test_color_auto.py | 177 +++++++++++++++++++++++ 8 files changed, 349 insertions(+), 17 deletions(-) create mode 100644 vectorizing/tests/images/test_logo.png create mode 100644 vectorizing/tests/test_color_auto.py diff --git a/README.md b/README.md index efa95ea..6533550 100644 --- a/README.md +++ b/README.md @@ -98,7 +98,7 @@ The request format is the following: { url: string, // Image URL solver: number, // Solver. 0 -> Binary, 1 -> Color - color_count: number, // Number of colors (if applicable) + color_count: number | "auto", // Number of colors, or choose 1–16 automatically (color solver only) configuration: string, // Optional color profile: "current" (default) or "experimental" raw: boolean // If true, plain return plain SVG markup } @@ -127,6 +127,8 @@ A typical response would be Or, if `raw = true` was supplied, just plain SVG markup +For color requests, set `color_count` to `"auto"` to estimate 1–16 dominant colors from the image (ignoring background pixels and small blended edges). When any pixel has zero alpha, pixels below half opacity are treated as background, matching color quantization. For example, `midnight_strike.png`, `geo_logo.png` and `test_logo.png` each select three. Auto compares octree and median-cut palettes to retain both vivid accents and subtly patterned backgrounds; numeric quantization is unchanged. Omitting `color_count` still defaults to six; numeric requests retain the existing 2–64 clamp. Automatic selection is a heuristic: very small accents may not contribute to the count. + Color processing can be selected per request with the optional `configuration` JSON field. The default `current` profile uses the original color quantization and layer clipping behavior. Set `configuration` to `experimental` to use the newer quantization, overlap-based layers, and opaque-background detection/isolation. The profiles are assembled from independently switchable solver stages, so behavior can be compared without removing either implementation. Unknown profile names are rejected with `INVALID_PARAMETERS`. The `experimental` profile's color processing uses a gentle 3-pixel bilateral filter and removes only connected @@ -136,7 +138,7 @@ the most common surviving perimeter color is also protected to retain small background-colored letter counters. This can retain extra small specks of that color. Tracing retains small paths and uses a curve optimization tolerance of 0.5. The existing 1,048,576-pixel area cap, default of six -colors and supported range of 2–64 colors are unchanged. Color paths touching the +colors and numeric range of 2–64 colors are unchanged. Color paths touching the canvas are extended before tracing and clipped back to the image so corners remain covered and returned bounds do not include the padding. If Skia rejects a canvas clip, that layer is retraced without padding and a warning is logged. Recovery diff --git a/vectorizing/__init__.py b/vectorizing/__init__.py index 1195a05..d33a25f 100644 --- a/vectorizing/__init__.py +++ b/vectorizing/__init__.py @@ -48,7 +48,7 @@ def process_binary(img: Image.Image) -> tuple[list[Path], list[list[int]], int, def process_color( img: Image.Image, - color_count: int | None, + color_count: int | str | None, timer: Timer, configuration: str = DEFAULT_CONFIGURATION, ) -> list[list[Path] | list[np.ndarray] | int]: @@ -69,6 +69,9 @@ def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: configuration = args.get("configuration", DEFAULT_CONFIGURATION) if not isinstance(configuration, str) or configuration not in CONFIGURATIONS: return False + color_count = args.get("color_count") + if solver == 1 and isinstance(color_count, str) and color_count not in ("auto", ""): + return False box = args.get("crop_box") if box: @@ -84,7 +87,7 @@ def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: solver=solver, url=args.get("url"), raw=args.get("raw"), - color_count=args.get("color_count"), + color_count=color_count, configuration=configuration, ) diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index b2920d9..9907b53 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -16,7 +16,11 @@ create_background_bitmap, create_bitmaps, ) -from vectorizing.solvers.color.quantize import quantize +from vectorizing.solvers.color.quantize import ( + auto_color_count, + get_background_cluster, + quantize, +) from vectorizing.util.limit_size import limit_size @@ -97,20 +101,36 @@ class ColorSolver: def __init__( self, img: Image.Image, - color_count: int | None, + color_count: int | str | None, timer: Timer, configuration: str = DEFAULT_CONFIGURATION, ) -> None: - color_count = color_count or ColorSolver.DEFAULT_COLOR_COUNT - color_count = max(color_count, ColorSolver.MIN_COLOR_COUNT) - color_count = min(color_count, ColorSolver.MAX_COLOR_COUNT) - self.color_count = color_count - self.img = limit_size(img) # Init image array self.img_arr = np.asarray(self.img).astype(np.uint8) + self.auto_method = None + if color_count == "auto": + background = ( + get_background_cluster(self.img_arr) + if self.img_arr.shape[-1] == 4 + else None + ) + self.color_count, representative, self.auto_method = auto_color_count( + self.img_arr, + background, + ) + if background is not None and representative is not None: + # Both quantizers cluster background RGB before masking it; + # give it a visible color so it cannot consume a palette slot. + self.img_arr = self.img_arr.copy() + self.img_arr[background > 0, :3] = representative + else: + color_count = color_count or ColorSolver.DEFAULT_COLOR_COUNT + color_count = max(color_count, ColorSolver.MIN_COLOR_COUNT) + self.color_count = min(color_count, ColorSolver.MAX_COLOR_COUNT) + self.timer = timer self.configuration = CONFIGURATIONS[configuration] @@ -120,7 +140,11 @@ def solve(self) -> list[list[Path] | list[np.ndarray] | int]: quantizer = ( legacy.quantize if self.configuration.original_quantization else quantize ) - labels, colors, has_background = quantizer(self.img_arr, self.color_count) + labels, colors, has_background = ( + quantizer(self.img_arr, self.color_count, auto_method=self.auto_method) + if self.auto_method is not None + else quantizer(self.img_arr, self.color_count) + ) self.timer.end_timer() self.timer.start_timer("Bitmap Creation") diff --git a/vectorizing/solvers/color/legacy.py b/vectorizing/solvers/color/legacy.py index 0abea64..de694a9 100644 --- a/vectorizing/solvers/color/legacy.py +++ b/vectorizing/solvers/color/legacy.py @@ -5,6 +5,7 @@ import potrace import scipy.ndimage as ndi from pathops import Path, PathOp, op +from PIL import Image from skimage.measure import label from vectorizing.geometry.potrace import potrace_path_to_compound_path @@ -18,6 +19,8 @@ def quantize( img_arr: np.ndarray, color_count: int, + *, + auto_method: Image.Quantize | None = None, ) -> tuple[np.ndarray, np.ndarray, bool]: """Run the original strong-filter and overlap-based component cleanup.""" background = get_background_cluster(img_arr) if img_arr.shape[-1] == 4 else None @@ -25,7 +28,12 @@ def quantize( cv2.cvtColor(img_arr, cv2.COLOR_RGBA2RGB) if img_arr.shape[-1] == 4 else img_arr ) rgb = cv2.bilateralFilter(rgb.copy(), 7, 50, 50) - labels, colors = kmeans(rgb, get_initial_centroids(rgb, color_count)) + centroids = ( + get_initial_centroids(rgb, color_count, auto_method) + if auto_method is not None + else get_initial_centroids(rgb, color_count) + ) + labels, colors = kmeans(rgb, centroids) labels = labels.reshape(rgb.shape[:2]) if background is not None: labels = np.where(background > 0, 0, labels + 1) diff --git a/vectorizing/solvers/color/quantize.py b/vectorizing/solvers/color/quantize.py index d38c1fb..30f2c89 100644 --- a/vectorizing/solvers/color/quantize.py +++ b/vectorizing/solvers/color/quantize.py @@ -10,6 +10,88 @@ MIN_COMPONENT_AREA = 8 +def auto_color_count( + img_arr: np.ndarray, + background: np.ndarray | None, +) -> tuple[int, np.ndarray | None, Image.Quantize]: + """Return color count, representative visible RGB and chosen seed method. + + Small sample palettes choose K and the K-means initialization method; the + selected profile still quantizes the full processed image with its own filter. + + Parameters + ---------- + img_arr : numpy.ndarray + Processed RGB or RGBA pixels. + background : numpy.ndarray or None + Nonzero at pixels that the quantizer treats as transparent background. + + Returns + ------- + tuple + Color count, representative RGB (or None), and seed method. + """ + pixels = ( + img_arr[background == 0, :3] + if background is not None + else img_arr[:, :, :3].reshape(-1, 3) + ) + if not len(pixels): + return 1, None, Image.Quantize.FASTOCTREE + if len(pixels) > 65536: + # Fixed-seed sampling avoids row-aligned strides hiding whole features. + indices = np.random.default_rng(0).choice(len(pixels), 65536, replace=False) + pixels = pixels[indices] + sample = Image.fromarray(pixels.reshape(1, -1, 3)) + best_count = 0 + representative = None + chosen_method = Image.Quantize.FASTOCTREE + # Octree keeps small vivid accents; median cut separates large close tones. + for method in (Image.Quantize.FASTOCTREE, Image.Quantize.MEDIANCUT): + palette_image = sample.quantize(16, method=method) + palette = np.asarray(palette_image.getpalette("RGB"), dtype=np.uint8).reshape( + -1, + 3, + ) + entries = sorted(palette_image.getcolors(), reverse=True) + dominant: list[np.ndarray] = [] + for size, index in entries: + share = size / len(pixels) + if share < 0.005: + continue + color = palette[index].astype(np.float32) + # Large, subtly different regions (e.g. a patterned background) + # matter even when their RGB distance is below the edge-shade cutoff. + separation = 8 if share >= 0.1 else 25 + if any(np.linalg.norm(color - other) < separation for other in dominant): + continue + # Small blended edge colors lie between two stronger colors; large + # intermediate regions can be real artwork and must keep their slot. + if share < 0.03 and any( + np.linalg.norm( + color + - first + - np.clip( + np.dot(color - first, second - first) + / np.dot(second - first, second - first), + 0, + 1, + ) + * (second - first), + ) + < 25 + for i, first in enumerate(dominant) + for second in dominant[i + 1 :] + ): + continue + dominant.append(color) + if len(dominant) > best_count: + best_count = len(dominant) + representative = palette[entries[0][1]] + chosen_method = method + return max(1, best_count), representative, chosen_method + + def bilateral_filter(img_arr: np.ndarray) -> np.ndarray: """Gently smooth local color noise without the broad blur of a large kernel.""" return cv2.bilateralFilter(img_arr, 3, 12, 1) @@ -105,10 +187,14 @@ def write_background_cluster(labels: np.ndarray, bg_cluster: np.ndarray) -> np.n return labels -def get_initial_centroids(img_arr: np.ndarray, color_count: int) -> np.ndarray: +def get_initial_centroids( + img_arr: np.ndarray, + color_count: int, + method: Image.Quantize = Image.Quantize.FASTOCTREE, +) -> np.ndarray: """Return sorted unique used RGB palette colors for K-means initialization.""" img = Image.fromarray(img_arr) - img = img.quantize(color_count, method=Image.Quantize.FASTOCTREE) + img = img.quantize(color_count, method=method) # Palette padding must not introduce additional clusters. RGB order affects # initialization, so sort the used entries rather than the entire pixel grid. used_indices = [index for _, index in img.getcolors()] @@ -133,11 +219,18 @@ def kmeans( def quantize( img_arr: np.ndarray, color_count: int, + *, + auto_method: Image.Quantize | None = None, ) -> tuple[np.ndarray, np.ndarray, bool]: """Return area-cleaned labels, an RGB-ordered palette and background status.""" background = get_background_cluster(img_arr) if img_arr.shape[-1] == 4 else None rgb = bilateral_filter(img_arr[:, :, :3].copy()) - labels, colors = kmeans(rgb, get_initial_centroids(rgb, color_count)) + centroids = ( + get_initial_centroids(rgb, color_count, auto_method) + if auto_method is not None + else get_initial_centroids(rgb, color_count) + ) + labels, colors = kmeans(rgb, centroids) labels = labels.reshape(rgb.shape[:2]) # Paint order determines which neighboring colors may receive a bounded rim. diff --git a/vectorizing/tests/images/test_logo.png 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zy9b&K9DlyMCyrhls5u)OQo*fAYQ2C8;Q!TPXtV)TK!Q{fZ*UJO9Vq_eztLnncARyHOiVy}l}ckROhLuRoa#80 z3Pi&$cJm820U?u-FZpMMWa}b(HRVI~j{*BzvFLJWa?RtnT3I=sq#qBuo+GSl)w=#X z5iHVq8*@TM=7uii?prC_jlVwcmP6=lQ*D@Mc04^dViqp3kPJh0UtV=a-Wp{STCvg} z8^r`7m$IG>NAFZJ&jqFKNlvc+a&I^JZ+4>d>W@4!;j7l50WTqGC6upoGjaUc%C$rq;fbUGcd;2RXP|1M(jZq2Shr z#@i{BVxe;$u=?o-r-#Lsao__abXQ__|NfWd7RnsdCY zoaTm^{Vlv`E+Hr-FqjKMvkbi=iO)le;X}rmn3#UtHMsS7oV5S0E5JrjMcmtXdd#ym zF}=p5v{=V?x~fD3Aj}}R`lYAt_{^oh{7z*r0?Q)zhTnz~TNBoNGizhw&sXROsb;TR z> None: + """Leave unrelated color fields alone on the binary request path.""" + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(return_value=Image.new("RGB", (8, 8))), + ) + response = client.post( + "/", + json={"url": "image", "solver": 0, "color_count": "ignored", "raw": True}, + ) + assert response.status_code == 200 + assert ( + response.data + == client.post("/", json={"url": "image", "solver": 0, "raw": True}).data + ) + + @pytest.mark.parametrize("solver", [0, 1]) def test_raw_requests_crop_before_vectorizing_and_do_not_upload( solver: int, diff --git a/vectorizing/tests/test_color_auto.py b/vectorizing/tests/test_color_auto.py new file mode 100644 index 0000000..0365d29 --- /dev/null +++ b/vectorizing/tests/test_color_auto.py @@ -0,0 +1,177 @@ +"""Choose automatic palette sizes without changing numeric mode.""" + +from io import BytesIO +from pathlib import Path +from unittest.mock import Mock + +import numpy as np +import pytest +from cairosvg import svg2png +from flask.testing import FlaskClient +from PIL import Image + +import vectorizing +from vectorizing.server.timer import Timer +from vectorizing.solvers.color.ColorSolver import ColorSolver +from vectorizing.svg.markup import generate_original_SVG_markup, generate_SVG_markup +from vectorizing.util.read import convert_RGB_A + + +@pytest.mark.parametrize( + "name, expected", + [ + # These artwork counts are contracts: never rebaseline them to fit a + # new heuristic. aftermath.png has too many colors to pin this way. + ("geo_logo.png", 3), + ("midnight_strike.png", 3), + ("shapes.png", 4), + ("shapes_2.png", 6), + ("test_logo.png", 3), + ("bubbles.png", 4), + ("black_rectangle.png", 1), + ("empty.png", 1), + ], +) +def test_auto_count_on_gallery(name: str, expected: int) -> None: + """Pin curated palette sizes while ignoring blended edge colors.""" + with Image.open(Path(__file__).parent / "images" / name) as source: + image = convert_RGB_A(source) + solver = ColorSolver(image, "auto", Timer()) + assert solver.color_count == expected + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_auto_traces_three_layers_on_midnight_strike(configuration: str) -> None: + """Pass the selected count through real quantization and layer tracing.""" + with Image.open(Path(__file__).parent / "images" / "midnight_strike.png") as source: + solver = ColorSolver(convert_RGB_A(source), "auto", Timer(), configuration) + paths, colors, _, _ = solver.solve() + assert solver.color_count == len(paths) == len(colors) == 3 + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_transparent_canvas_does_not_take_a_color_slot(configuration: str) -> None: + """Hidden black must not desaturate two opaque colors on a transparent logo.""" + pixels = np.zeros((128, 128, 4), dtype=np.uint8) + pixels[16:64, 16:64] = (255, 0, 0, 255) + pixels[64:112, 64:112] = (0, 0, 255, 255) + pixels[0, 0] = (0, 255, 0, 1) # A rare edge must not dominate hidden RGB. + solver = ColorSolver(Image.fromarray(pixels), "auto", Timer(), configuration) + _, colors, _, _ = solver.solve() + assert solver.color_count == 2 + assert {tuple(color[:3]) for color in colors} == {(255, 0, 0), (0, 0, 255)} + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_thin_strokes_between_grid_points_keep_both_colors(configuration: str) -> None: + """Transparent line art cannot vanish just because its columns miss a grid.""" + pixels = np.zeros((1024, 1024, 4), dtype=np.uint8) + pixels[:, 1:4] = (255, 0, 0, 255) + pixels[:, 5:8] = (0, 0, 255, 255) + solver = ColorSolver(Image.fromarray(pixels), "auto", Timer(), configuration) + _, colors, _, _ = solver.solve() + assert solver.color_count == 2 + assert {tuple(color[:3]) for color in colors} == {(255, 0, 0), (0, 0, 255)} + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_visible_pixel_sampling_cannot_lock_to_background_columns( + configuration: str, +) -> None: + """A single transparent pixel must not phase-lock sampling away from stripes.""" + pixels = np.full((1024, 1024, 4), 255, dtype=np.uint8) + pixels[:, 5::16, :3] = (255, 0, 0) + pixels[:, 6::16, :3] = (255, 0, 0) + pixels[:, 7::16, :3] = (255, 0, 0) + pixels[0, 0] = (0, 0, 0, 0) + solver = ColorSolver(Image.fromarray(pixels), "auto", Timer(), configuration) + _, colors, _, _ = solver.solve() + assert solver.color_count == 2 + expected = {(255, 255, 255), (255, 0, 0)} + assert {tuple(color[:3]) for color in colors} == expected + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_shadow_masked_by_background_does_not_take_a_slot( + configuration: str, +) -> None: + """An alpha-60 shadow becomes background when the image also has alpha 0.""" + pixels = np.zeros((128, 128, 4), dtype=np.uint8) + pixels[8:64, 8:64] = (255, 0, 0, 255) + pixels[64:120, 64:120] = (0, 0, 255, 255) + pixels[8:64, 64:120] = (0, 255, 0, 60) + solver = ColorSolver(Image.fromarray(pixels), "auto", Timer(), configuration) + _, colors, _, _ = solver.solve() + assert solver.color_count == 2 + assert {tuple(color[:3]) for color in colors} == {(255, 0, 0), (0, 0, 255)} + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_geo_logo_pattern_is_a_separate_layer(configuration: str) -> None: + """Keep both large pale regions separate from each other and the dark logo.""" + with Image.open(Path(__file__).parent / "images" / "geo_logo.png") as source: + solver = ColorSolver(convert_RGB_A(source), "auto", Timer(), configuration) + paths, colors, width, height = solver.solve() + assert solver.color_count == len(paths) == len(colors) == 3 + pale = [color[:3] for color in colors if np.min(color[:3]) > 200] + assert len(pale) == 2 + assert np.linalg.norm(pale[0].astype(int) - pale[1].astype(int)) >= 5 + serialize = ( + generate_original_SVG_markup + if configuration == "current" + else generate_SVG_markup + ) + markup = serialize(paths, colors, width, height) + raster = Image.open(BytesIO(svg2png(bytestring=markup.encode()))).convert("RGB") + assert raster.getpixel((0, 0)) != raster.getpixel((150, 0)) + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_kittl_logo_accent_has_its_own_layer(configuration: str) -> None: + """Preserve the small neon mark as well as black lettering and white canvas.""" + with Image.open(Path(__file__).parent / "images" / "test_logo.png") as source: + solver = ColorSolver(convert_RGB_A(source), "auto", Timer(), configuration) + paths, colors, _, _ = solver.solve() + assert solver.color_count == len(paths) == len(colors) == 3 + assert any(160 < color[1] and color[2] < 120 for color in colors) + + +def test_large_intermediate_color_is_not_treated_as_an_edge() -> None: + """An entire gray panel between black and white is a third color.""" + pixels = np.zeros((100, 100, 3), dtype=np.uint8) + pixels[40:75] = (255, 255, 255) + pixels[75:] = (128, 128, 128) + assert ColorSolver(Image.fromarray(pixels), "auto", Timer()).color_count == 3 + + +def test_partially_transparent_pixels_count_as_visible() -> None: + """The solver clusters nonzero-alpha RGB, so auto must count it too.""" + pixels = np.zeros((100, 100, 4), dtype=np.uint8) + pixels[:50] = (255, 0, 0, 64) + pixels[50:] = (0, 0, 255, 255) + assert ColorSolver(Image.fromarray(pixels), "auto", Timer()).color_count == 2 + + +def test_auto_request_and_numeric_default_remain_distinct( + client: FlaskClient, + monkeypatch: pytest.MonkeyPatch, +) -> None: + """Only the explicit auto string opts into estimation; numeric clamps remain.""" + monkeypatch.setattr( + vectorizing, + "try_read_image_from_url", + Mock(return_value=Image.new("RGB", (8, 8))), + ) + process = Mock(return_value=([], [], 8, 8)) + monkeypatch.setattr(vectorizing, "process_color", process) + for count in ["auto", None, "", 1, 65]: + response = client.post( + "/", + json={"url": "image", "solver": 1, "raw": True, "color_count": count}, + ) + assert response.status_code == 200 + assert process.call_args.args[1] == count + assert ColorSolver(Image.new("RGB", (8, 8)), None, Timer()).color_count == 6 + assert ColorSolver(Image.new("RGB", (8, 8)), 1, Timer()).color_count == 2 + assert ColorSolver(Image.new("RGB", (8, 8)), 65, Timer()).color_count == 64 + assert ColorSolver(Image.new("RGB", (8, 8)), "", Timer()).color_count == 6 From 716a59dde1ef189a50b68157e5611f8822a0a5ea Mon Sep 17 00:00:00 2001 From: Phil Rukin Date: Tue, 29 Sep 2026 15:14:20 +0200 Subject: [PATCH 16/16] feat(color): trace single-color auto artwork as binary (#89) --- README.md | 2 + vectorizing/__init__.py | 8 ++-- vectorizing/solvers/color/ColorSolver.py | 8 +++- vectorizing/tests/test_api_contracts.py | 13 ++++++- vectorizing/tests/test_color_auto.py | 47 ++++++++++++++++++++++++ 5 files changed, 73 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 6533550..6b5d2c7 100644 --- a/README.md +++ b/README.md @@ -129,6 +129,8 @@ Or, if `raw = true` was supplied, just plain SVG markup For color requests, set `color_count` to `"auto"` to estimate 1–16 dominant colors from the image (ignoring background pixels and small blended edges). When any pixel has zero alpha, pixels below half opacity are treated as background, matching color quantization. For example, `midnight_strike.png`, `geo_logo.png` and `test_logo.png` each select three. Auto compares octree and median-cut palettes to retain both vivid accents and subtly patterned backgrounds; numeric quantization is unchanged. Omitting `color_count` still defaults to six; numeric requests retain the existing 2–64 clamp. Automatic selection is a heuristic: very small accents may not contribute to the count. +When auto selects one visible color, the binary solver traces it as black on transparent; an entirely transparent image remains empty. Auto requests use the color solver: omitting `solver` selects it, while explicitly sending `solver: 0` with `"auto"` is rejected rather than silently running a binary job. + Color processing can be selected per request with the optional `configuration` JSON field. The default `current` profile uses the original color quantization and layer clipping behavior. Set `configuration` to `experimental` to use the newer quantization, overlap-based layers, and opaque-background detection/isolation. The profiles are assembled from independently switchable solver stages, so behavior can be compared without removing either implementation. Unknown profile names are rejected with `INVALID_PARAMETERS`. The `experimental` profile's color processing uses a gentle 3-pixel bilateral filter and removes only connected diff --git a/vectorizing/__init__.py b/vectorizing/__init__.py index d33a25f..342c889 100644 --- a/vectorizing/__init__.py +++ b/vectorizing/__init__.py @@ -51,7 +51,7 @@ def process_color( color_count: int | str | None, timer: Timer, configuration: str = DEFAULT_CONFIGURATION, -) -> list[list[Path] | list[np.ndarray] | int]: +) -> list[list[Path] | list[np.ndarray] | list[list[int]] | int]: """Trace color layers using a named processing configuration.""" solver = ColorSolver(img, color_count, timer, configuration) return solver.solve() @@ -62,14 +62,16 @@ def validate_args(args: dict[str, object]) -> SimpleNamespace | Literal[False]: if "url" not in args: return False - solver = args.get("solver", DEFAULT_SOLVER) + color_count = args.get("color_count") + solver = args.get("solver", 1 if color_count == "auto" else DEFAULT_SOLVER) if solver not in SOLVERS: return False configuration = args.get("configuration", DEFAULT_CONFIGURATION) if not isinstance(configuration, str) or configuration not in CONFIGURATIONS: return False - color_count = args.get("color_count") + if solver == 0 and color_count == "auto": + return False if solver == 1 and isinstance(color_count, str) and color_count not in ("auto", ""): return False diff --git a/vectorizing/solvers/color/ColorSolver.py b/vectorizing/solvers/color/ColorSolver.py index 9907b53..24dfa89 100644 --- a/vectorizing/solvers/color/ColorSolver.py +++ b/vectorizing/solvers/color/ColorSolver.py @@ -10,6 +10,7 @@ from vectorizing.geometry.potrace import potrace_path_to_compound_path from vectorizing.server.timer import Timer +from vectorizing.solvers.binary.BinarySolver import BinarySolver from vectorizing.solvers.color import legacy from vectorizing.solvers.color.bitmaps import ( add_bitmap_rims, @@ -111,6 +112,7 @@ def __init__( self.img_arr = np.asarray(self.img).astype(np.uint8) self.auto_method = None + self.binary_fallback = False if color_count == "auto": background = ( get_background_cluster(self.img_arr) @@ -121,6 +123,7 @@ def __init__( self.img_arr, background, ) + self.binary_fallback = self.color_count == 1 and representative is not None if background is not None and representative is not None: # Both quantizers cluster background RGB before masking it; # give it a visible color so it cannot consume a palette slot. @@ -134,8 +137,11 @@ def __init__( self.timer = timer self.configuration = CONFIGURATIONS[configuration] - def solve(self) -> list[list[Path] | list[np.ndarray] | int]: + def solve(self) -> list[list[Path] | list[np.ndarray] | list[list[int]] | int]: """Return paths, colors, width and height as a list.""" + if self.binary_fallback: + return list(BinarySolver(self.img).solve()) + self.timer.start_timer("Quantization") quantizer = ( legacy.quantize if self.configuration.original_quantization else quantize diff --git a/vectorizing/tests/test_api_contracts.py b/vectorizing/tests/test_api_contracts.py index dbfec37..e8e980a 100644 --- a/vectorizing/tests/test_api_contracts.py +++ b/vectorizing/tests/test_api_contracts.py @@ -24,6 +24,7 @@ {"url": "image", "configuration": None}, {"url": "image", "configuration": []}, {"url": "image", "solver": 1, "color_count": "automatic"}, + {"url": "image", "solver": 0, "color_count": "auto"}, ], ) def test_invalid_arguments_return_the_same_error( @@ -59,7 +60,10 @@ def test_argument_validation_preserves_accepted_values( assert isinstance(result, SimpleNamespace) assert vars(result) == { "url": payload["url"], - "solver": payload.get("solver", 0), + "solver": payload.get( + "solver", + 1 if payload.get("color_count") == "auto" else 0, + ), "crop_box": payload.get("crop_box"), "raw": None, "color_count": payload.get("color_count"), @@ -67,6 +71,13 @@ def test_argument_validation_preserves_accepted_values( } +def test_omitted_solver_with_auto_selects_color() -> None: + """Do not silently treat an auto-only request as a binary request.""" + args = vectorizing.validate_args({"url": "image", "color_count": "auto"}) + assert isinstance(args, SimpleNamespace) + assert args.solver == 1 + + def test_binary_ignores_string_color_count( client: FlaskClient, monkeypatch: pytest.MonkeyPatch, diff --git a/vectorizing/tests/test_color_auto.py b/vectorizing/tests/test_color_auto.py index 0365d29..3380e34 100644 --- a/vectorizing/tests/test_color_auto.py +++ b/vectorizing/tests/test_color_auto.py @@ -12,6 +12,7 @@ import vectorizing from vectorizing.server.timer import Timer +from vectorizing.solvers.binary.BinarySolver import BinarySolver from vectorizing.solvers.color.ColorSolver import ColorSolver from vectorizing.svg.markup import generate_original_SVG_markup, generate_SVG_markup from vectorizing.util.read import convert_RGB_A @@ -136,6 +137,52 @@ def test_kittl_logo_accent_has_its_own_layer(configuration: str) -> None: assert any(160 < color[1] and color[2] < 120 for color in colors) +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_visible_single_color_auto_traces_with_binary_solver( + configuration: str, +) -> None: + """Turn white text on transparent canvas into a black transparent SVG.""" + with Image.open(Path(__file__).parent / "images" / "white_text.png") as source: + image = convert_RGB_A(source) + solver = ColorSolver(image, "auto", Timer(), configuration) + actual = solver.solve() + expected = BinarySolver(image).solve() + serialize = ( + generate_original_SVG_markup + if configuration == "current" + else generate_SVG_markup + ) + assert isinstance(actual, list) + assert solver.color_count == 1 + assert actual[1] == [[0, 0, 0, 1]] + assert serialize(*actual) == serialize(*expected) + raster = Image.open( + BytesIO(svg2png(bytestring=serialize(*actual).encode())), + ).convert("RGBA") + assert raster.getchannel("A").getextrema() == (0, 255) + + +@pytest.mark.parametrize("configuration", ["current", "experimental"]) +def test_fully_transparent_auto_does_not_trace_a_black_rectangle( + configuration: str, +) -> None: + """No visible color means there is no artwork for the binary fallback.""" + with Image.open(Path(__file__).parent / "images" / "empty.png") as source: + solver = ColorSolver(convert_RGB_A(source), "auto", Timer(), configuration) + paths, colors, width, height = solver.solve() + assert solver.color_count == 1 + assert paths == colors == [] + serialize = ( + generate_original_SVG_markup + if configuration == "current" + else generate_SVG_markup + ) + raster = Image.open( + BytesIO(svg2png(bytestring=serialize(paths, colors, width, height).encode())), + ).convert("RGBA") + assert raster.getchannel("A").getextrema() == (0, 0) + + def test_large_intermediate_color_is_not_treated_as_an_edge() -> None: """An entire gray panel between black and white is a third color.""" pixels = np.zeros((100, 100, 3), dtype=np.uint8)