|
9 | 9 |
|
10 | 10 | import pytest |
11 | 11 |
|
12 | | -from PIL import Image, ImageFilter |
| 12 | +from PIL import Image, ImageChops, ImageFilter |
13 | 13 | from PIL.Image import Resampling, Transpose |
14 | 14 |
|
15 | 15 | TYPE_CHECKING = False |
@@ -341,3 +341,140 @@ def test_merge(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> Non |
341 | 341 | bands = im.split() |
342 | 342 | bench.extra_info["label"] = [f"merge {mode}"] |
343 | 343 | bench(Image.merge, mode, bands) |
| 344 | + |
| 345 | + |
| 346 | +@pytest.mark.benchmark(group="allocate") |
| 347 | +@pytest.mark.parametrize("mode", MODES) |
| 348 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 349 | +def test_fill(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 350 | + nbands = len(Image.new(mode, (1, 1)).getbands()) |
| 351 | + color = (10, 20, 30, 40)[:nbands] if nbands > 1 else 10 |
| 352 | + bench.extra_info["label"] = [f"fill {mode}"] |
| 353 | + bench(Image.new, mode, size, color) |
| 354 | + |
| 355 | + |
| 356 | +CHOPS_OPS = [ |
| 357 | + ImageChops.add, |
| 358 | + ImageChops.subtract, |
| 359 | + ImageChops.multiply, |
| 360 | + ImageChops.screen, |
| 361 | + ImageChops.difference, |
| 362 | + ImageChops.lighter, |
| 363 | + ImageChops.darker, |
| 364 | + ImageChops.add_modulo, |
| 365 | + ImageChops.soft_light, |
| 366 | + ImageChops.hard_light, |
| 367 | + ImageChops.overlay, |
| 368 | +] |
| 369 | + |
| 370 | + |
| 371 | +@pytest.mark.benchmark(group="chops") |
| 372 | +@pytest.mark.parametrize("op", CHOPS_OPS, ids=lambda f: f.__name__) |
| 373 | +@pytest.mark.parametrize("mode", MODES) |
| 374 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 375 | +def test_chops( |
| 376 | + bench: BenchmarkFixture, |
| 377 | + mode: str, |
| 378 | + size: tuple[int, int], |
| 379 | + op: str, |
| 380 | +) -> None: |
| 381 | + im1 = make_pillow_image(mode, size) |
| 382 | + im2 = make_pillow_image(mode, size, pattern_offset=1024) |
| 383 | + bench.extra_info["label"] = [op.__name__] |
| 384 | + result = bench(op, im1, im2) |
| 385 | + assert result.size == im1.size |
| 386 | + |
| 387 | + |
| 388 | +@pytest.mark.benchmark(group="chops") |
| 389 | +@pytest.mark.parametrize("mode", MODES) |
| 390 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 391 | +def test_invert(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 392 | + im = make_pillow_image(mode, size) |
| 393 | + bench.extra_info["label"] = ["invert"] |
| 394 | + bench(ImageChops.invert, im) |
| 395 | + |
| 396 | + |
| 397 | +@pytest.mark.benchmark(group="chops") |
| 398 | +@pytest.mark.parametrize("mode", MODES) |
| 399 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 400 | +def test_offset(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 401 | + im = make_pillow_image(mode, size) |
| 402 | + bench.extra_info["label"] = ["offset"] |
| 403 | + bench(ImageChops.offset, im, 123, 45) |
| 404 | + |
| 405 | + |
| 406 | +@pytest.mark.benchmark(group="histogram") |
| 407 | +@pytest.mark.parametrize("mode", MODES) |
| 408 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 409 | +def test_histogram(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 410 | + im = make_pillow_image(mode, size) |
| 411 | + bench.extra_info["label"] = [f"histogram {mode}"] |
| 412 | + bench(im.histogram) |
| 413 | + |
| 414 | + |
| 415 | +@pytest.mark.benchmark(group="histogram") |
| 416 | +@pytest.mark.parametrize("mode", MODES) |
| 417 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 418 | +def test_histogram_masked( |
| 419 | + bench: BenchmarkFixture, mode: str, size: tuple[int, int] |
| 420 | +) -> None: |
| 421 | + im = make_pillow_image(mode, size) |
| 422 | + mask = make_pillow_image("L", size) |
| 423 | + bench.extra_info["label"] = [f"masked histogram {mode}"] |
| 424 | + bench(im.histogram, mask) |
| 425 | + |
| 426 | + |
| 427 | +L_MATRIX = (0.299, 0.587, 0.114, 0.0) |
| 428 | +RGB_MATRIX = ( |
| 429 | + 0.412, 0.357, 0.180, 0.0, |
| 430 | + 0.212, 0.715, 0.072, 0.0, |
| 431 | + 0.019, 0.119, 0.950, 0.0, |
| 432 | +) # fmt: skip |
| 433 | + |
| 434 | + |
| 435 | +@pytest.mark.benchmark(group="convert") |
| 436 | +@pytest.mark.parametrize( |
| 437 | + "mode_to, matrix", |
| 438 | + [("L", L_MATRIX), ("RGB", RGB_MATRIX)], |
| 439 | +) |
| 440 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 441 | +def test_matrix_convert( |
| 442 | + bench: BenchmarkFixture, |
| 443 | + mode_to: str, |
| 444 | + matrix: tuple[float, ...], |
| 445 | + size: tuple[int, int], |
| 446 | +) -> None: |
| 447 | + im = make_pillow_image("RGB", size) |
| 448 | + bench.extra_info["label"] = [f"matrix RGB to {mode_to}"] |
| 449 | + bench(im.convert, mode_to, matrix) |
| 450 | + |
| 451 | + |
| 452 | +@pytest.mark.benchmark(group="point") |
| 453 | +@pytest.mark.parametrize("mode", MODES) |
| 454 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 455 | +def test_point_lut(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 456 | + im = make_pillow_image(mode, size) |
| 457 | + lut = [255 - i for i in range(256)] * len(im.getbands()) |
| 458 | + bench.extra_info["label"] = [f"LUT {mode}"] |
| 459 | + bench(im.point, lut) |
| 460 | + |
| 461 | + |
| 462 | +@pytest.mark.benchmark(group="point") |
| 463 | +@pytest.mark.parametrize("mode", ["I", "F"]) |
| 464 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 465 | +def test_point_transform( |
| 466 | + bench: BenchmarkFixture, mode: str, size: tuple[int, int] |
| 467 | +) -> None: |
| 468 | + im = make_pillow_image(mode, size) |
| 469 | + bench.extra_info["label"] = [f"transform {mode}"] |
| 470 | + bench(im.point, lambda v: v * 1.5 + 3.0) |
| 471 | + |
| 472 | + |
| 473 | +@pytest.mark.benchmark(group="quantize") |
| 474 | +@pytest.mark.parametrize("mode", [m for m in MODES if m in ("L", "RGB", "RGBA")]) |
| 475 | +@pytest.mark.parametrize("size", SIZES, ids=_format_size) |
| 476 | +def test_quantize(bench: BenchmarkFixture, mode: str, size: tuple[int, int]) -> None: |
| 477 | + im = make_pillow_image(mode, size) |
| 478 | + bench.extra_info["label"] = [f"quantize {mode}"] |
| 479 | + result = bench(im.quantize, 256) |
| 480 | + assert result.mode == "P" |
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