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Merged
merged 18 commits into from
Sep 27, 2021
Merged

Added gray image support to adjust_saturation function #4480

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11ee0d6
update channels parameter to every calling to check_functional_vs_PIL…
VinhLoiIT Sep 24, 2021
4f418a2
update adjust_saturation
VinhLoiIT Sep 24, 2021
05e632f
update docstrings for functional transformations
VinhLoiIT Sep 24, 2021
91ddf00
parametrize channels
VinhLoiIT Sep 24, 2021
ca9d332
update docstring of ColorJitter class
VinhLoiIT Sep 24, 2021
b0d6e17
move channels to class's parameter
VinhLoiIT Sep 24, 2021
acc7698
remove testing channels for geometric transforms
VinhLoiIT Sep 24, 2021
bcebeaf
revert redundant changes
VinhLoiIT Sep 24, 2021
d9d0a9d
revert redundant changes
VinhLoiIT Sep 24, 2021
8db48c4
update grayscale test cases for randaugment, autoaugment, trivialaugment
VinhLoiIT Sep 25, 2021
98f4753
update docstrings of randaugment, autoaugment, trivialaugment
VinhLoiIT Sep 25, 2021
5e58eeb
Merge remote-tracking branch 'upstream/main' into fix-adjust-functions
VinhLoiIT Sep 25, 2021
491d2b4
update docstring of ColorJitter
VinhLoiIT Sep 25, 2021
4cda359
fix adjust_hue's docstring
VinhLoiIT Sep 26, 2021
33ff265
change test equal tolerance
VinhLoiIT Sep 27, 2021
8d72386
Merge remote-tracking branch 'upstream/main' into fix-adjust-functions
VinhLoiIT Sep 27, 2021
da15495
refactor grayscale tests
VinhLoiIT Sep 27, 2021
c827a12
make get_grayscale_test_image private
VinhLoiIT Sep 27, 2021
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2 changes: 1 addition & 1 deletion test/common_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -148,7 +148,7 @@ def _create_data_batch(height=3, width=3, channels=3, num_samples=4, device="cpu
return batch_tensor


assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0)
assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=1e-6)


def get_list_of_videos(tmpdir, num_videos=5, sizes=None, fps=None):
Expand Down
48 changes: 35 additions & 13 deletions test/test_functional_tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -681,57 +681,65 @@ def check_functional_vs_PIL_vs_scripted(
@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"brightness_factor": f} for f in (0.1, 0.5, 1.0, 1.34, 2.5)])
def test_adjust_brightness(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_adjust_brightness(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.adjust_brightness,
F_pil.adjust_brightness,
F_t.adjust_brightness,
config,
device,
dtype,
channels,
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
def test_invert(device, dtype):
@pytest.mark.parametrize('channels', [1, 3])
def test_invert(device, dtype, channels):
check_functional_vs_PIL_vs_scripted(
F.invert,
F_pil.invert,
F_t.invert,
{},
device,
dtype,
channels,
tol=1.0,
agg_method="max"
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('config', [{"bits": bits} for bits in range(0, 8)])
def test_posterize(device, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_posterize(device, config, channels):
check_functional_vs_PIL_vs_scripted(
F.posterize,
F_pil.posterize,
F_t.posterize,
config,
device,
dtype=None,
channels=channels,
tol=1.0,
agg_method="max",
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('config', [{"threshold": threshold} for threshold in [0, 64, 128, 192, 255]])
def test_solarize1(device, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_solarize1(device, config, channels):
check_functional_vs_PIL_vs_scripted(
F.solarize,
F_pil.solarize,
F_t.solarize,
config,
device,
dtype=None,
channels=channels,
tol=1.0,
agg_method="max",
)
Expand All @@ -740,14 +748,16 @@ def test_solarize1(device, config):
@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"threshold": threshold} for threshold in [0.0, 0.25, 0.5, 0.75, 1.0]])
def test_solarize2(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_solarize2(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.solarize,
lambda img, threshold: F_pil.solarize(img, 255 * threshold),
F_t.solarize,
config,
device,
dtype,
channels,
tol=1.0,
agg_method="max",
)
Expand All @@ -756,34 +766,39 @@ def test_solarize2(device, dtype, config):
@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"sharpness_factor": f} for f in [0.2, 0.5, 1.0, 1.5, 2.0]])
def test_adjust_sharpness(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_adjust_sharpness(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.adjust_sharpness,
F_pil.adjust_sharpness,
F_t.adjust_sharpness,
config,
device,
dtype,
channels,
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
def test_autocontrast(device, dtype):
@pytest.mark.parametrize('channels', [1, 3])
def test_autocontrast(device, dtype, channels):
check_functional_vs_PIL_vs_scripted(
F.autocontrast,
F_pil.autocontrast,
F_t.autocontrast,
{},
device,
dtype,
channels,
tol=1.0,
agg_method="max"
)


@pytest.mark.parametrize('device', cpu_and_gpu())
def test_equalize(device):
@pytest.mark.parametrize('channels', [1, 3])
def test_equalize(device, channels):
torch.use_deterministic_algorithms(False)
check_functional_vs_PIL_vs_scripted(
F.equalize,
Expand All @@ -792,6 +807,7 @@ def test_equalize(device):
{},
device,
dtype=None,
channels=channels,
tol=1.0,
agg_method="max",
)
Expand All @@ -809,35 +825,39 @@ def test_adjust_contrast(device, dtype, config, channels):
config,
device,
dtype,
channels=channels
channels
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"saturation_factor": f} for f in [0.5, 0.75, 1.0, 1.5, 2.0]])
def test_adjust_saturation(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_adjust_saturation(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.adjust_saturation,
F_pil.adjust_saturation,
F_t.adjust_saturation,
config,
device,
dtype
dtype,
channels
)


@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"hue_factor": f} for f in [-0.45, -0.25, 0.0, 0.25, 0.45]])
def test_adjust_hue(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_adjust_hue(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.adjust_hue,
F_pil.adjust_hue,
F_t.adjust_hue,
config,
device,
dtype,
channels,
tol=16.1,
agg_method="max"
)
Expand All @@ -846,14 +866,16 @@ def test_adjust_hue(device, dtype, config):
@pytest.mark.parametrize('device', cpu_and_gpu())
@pytest.mark.parametrize('dtype', (None, torch.float32, torch.float64))
@pytest.mark.parametrize('config', [{"gamma": g1, "gain": g2} for g1, g2 in zip([0.8, 1.0, 1.2], [0.7, 1.0, 1.3])])
def test_adjust_gamma(device, dtype, config):
@pytest.mark.parametrize('channels', [1, 3])
def test_adjust_gamma(device, dtype, config, channels):
check_functional_vs_PIL_vs_scripted(
F.adjust_gamma,
F_pil.adjust_gamma,
F_t.adjust_gamma,
config,
device,
dtype,
channels,
)


Expand Down
21 changes: 18 additions & 3 deletions test/test_transforms.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,12 @@
os.path.dirname(os.path.abspath(__file__)), 'assets', 'encode_jpeg', 'grace_hopper_517x606.jpg')


def _get_grayscale_test_image(img, fill=None):
img = img.convert('L')
fill = (fill[0], ) if isinstance(fill, tuple) else fill
return img, fill


class TestConvertImageDtype:
@pytest.mark.parametrize('input_dtype, output_dtype', cycle_over(float_dtypes()))
def test_float_to_float(self, input_dtype, output_dtype):
Expand Down Expand Up @@ -1482,9 +1488,12 @@ def test_five_crop(single_dim):

@pytest.mark.parametrize('policy', transforms.AutoAugmentPolicy)
@pytest.mark.parametrize('fill', [None, 85, (128, 128, 128)])
def test_autoaugment(policy, fill):
@pytest.mark.parametrize('grayscale', [True, False])
def test_autoaugment(policy, fill, grayscale):
random.seed(42)
img = Image.open(GRACE_HOPPER)
if grayscale:
img, fill = _get_grayscale_test_image(img, fill)
transform = transforms.AutoAugment(policy=policy, fill=fill)
for _ in range(100):
img = transform(img)
Expand All @@ -1494,9 +1503,12 @@ def test_autoaugment(policy, fill):
@pytest.mark.parametrize('num_ops', [1, 2, 3])
@pytest.mark.parametrize('magnitude', [7, 9, 11])
@pytest.mark.parametrize('fill', [None, 85, (128, 128, 128)])
def test_randaugment(num_ops, magnitude, fill):
@pytest.mark.parametrize('grayscale', [True, False])
def test_randaugment(num_ops, magnitude, fill, grayscale):
random.seed(42)
img = Image.open(GRACE_HOPPER)
if grayscale:
img, fill = _get_grayscale_test_image(img, fill)
transform = transforms.RandAugment(num_ops=num_ops, magnitude=magnitude, fill=fill)
for _ in range(100):
img = transform(img)
Expand All @@ -1505,9 +1517,12 @@ def test_randaugment(num_ops, magnitude, fill):

@pytest.mark.parametrize('fill', [None, 85, (128, 128, 128)])
@pytest.mark.parametrize('num_magnitude_bins', [10, 13, 30])
def test_trivialaugmentwide(fill, num_magnitude_bins):
@pytest.mark.parametrize('grayscale', [True, False])
def test_trivialaugmentwide(fill, num_magnitude_bins, grayscale):
random.seed(42)
img = Image.open(GRACE_HOPPER)
if grayscale:
img, fill = _get_grayscale_test_image(img, fill)
transform = transforms.TrivialAugmentWide(fill=fill, num_magnitude_bins=num_magnitude_bins)
for _ in range(100):
img = transform(img)
Expand Down
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