def test_random_resized_crop_lazy(self):
target_keys = ['imgs', 'crop_bbox', 'img_shape', 'lazy']
# There will be a slight difference because of rounding
eps = 0.01
imgs = list(np.random.rand(2, 256, 341, 3))
results = dict(imgs=imgs)
with pytest.raises(AssertionError):
# area_range[0] > area_range[1], which is wrong
random_crop = RandomResizedCrop(area_range=(0.9, 0.7), lazy=True)
random_crop(results)
with pytest.raises(AssertionError):
# 0 > area_range[0] and area_range[1] > 1, which is wrong
random_crop = RandomResizedCrop(aspect_ratio_range=(-0.1, 2.0),
lazy=True)
random_crop(results)
random_crop = RandomResizedCrop(lazy=True)
random_crop_result = random_crop(results)
assert assert_dict_has_keys(random_crop_result, target_keys)
assert id(imgs) == id(random_crop_result['imgs'])
random_crop_result_fuse = Fuse()(random_crop_result)
assert check_crop(imgs, random_crop_result_fuse['imgs'],
results['crop_bbox'])
h, w = random_crop_result['img_shape']
assert ((0.08 - eps <= h * w / 256 / 341)
and (h * w / 256 / 341 <= 1 + eps))
assert (3. / 4. - eps <= h / w) and (h / w - eps <= 4. / 3.)
assert repr(random_crop) == (f'{random_crop.__class__.__name__}'
f'(area_range={(0.08, 1.0)}, '
f'aspect_ratio_range={(3 / 4, 4 / 3)}, '
f'lazy={True})')
random_crop = RandomResizedCrop(area_range=(0.9, 0.9),
aspect_ratio_range=(10.0, 10.1),
lazy=True)
# Test fallback cases by very big area range
imgs = np.random.rand(2, 256, 341, 3)
results = dict(imgs=imgs)
random_crop_result = random_crop(results)
assert assert_dict_has_keys(random_crop_result, target_keys)
assert id(imgs) == id(random_crop_result['imgs'])
random_crop_result_fuse = Fuse()(random_crop_result)
assert check_crop(imgs, random_crop_result_fuse['imgs'],
results['crop_bbox'])
h, w = random_crop_result['img_shape']
assert h == w == 256
def test_random_resized_crop():
with pytest.raises(TypeError):
# area_range must be a tuple of float
RandomResizedCrop(area_range=0.5)
with pytest.raises(TypeError):
# aspect_ratio_range must be a tuple of float
RandomResizedCrop(area_range=(0.08, 1.0), aspect_ratio_range=0.1)
target_keys = ['imgs', 'crop_bbox', 'img_shape']
# There will be a slight difference because of rounding
eps = 0.01
imgs = list(np.random.rand(2, 256, 341, 3))
results = dict(imgs=imgs)
results['gt_bboxes'] = np.array([[0, 0, 340, 256]])
results['proposals'] = np.array([[0, 0, 340, 256]])
kp = np.array([[160, 120], [160, 120]]).reshape([1, 1, 2, 2])
results['keypoint'] = kp
with pytest.raises(AssertionError):
# area_range[0] > area_range[1], which is wrong
random_crop = RandomResizedCrop(area_range=(0.9, 0.7))
random_crop(results)
with pytest.raises(AssertionError):
# 0 > area_range[0] and area_range[1] > 1, which is wrong
random_crop = RandomResizedCrop(aspect_ratio_range=(-0.1, 2.0))
random_crop(results)
random_crop = RandomResizedCrop()
random_crop_result = random_crop(results)
assert assert_dict_has_keys(random_crop_result, target_keys)
assert check_crop(imgs, random_crop_result['imgs'],
results['crop_bbox'])
h, w = random_crop_result['img_shape']
assert ((0.08 - eps <= h * w / 256 / 341)
and (h * w / 256 / 341 <= 1 + eps))
assert (3. / 4. - eps <= h / w) and (h / w - eps <= 4. / 3.)
assert repr(random_crop) == (f'{random_crop.__class__.__name__}'
f'(area_range={(0.08, 1.0)}, '
f'aspect_ratio_range={(3 / 4, 4 / 3)}, '
f'lazy={False})')
random_crop = RandomResizedCrop(area_range=(0.9, 0.9),
aspect_ratio_range=(10.0, 10.1))
# Test fallback cases by very big area range
imgs = list(np.random.rand(2, 256, 341, 3))
results = dict(imgs=imgs)
random_crop_result = random_crop(results)
assert assert_dict_has_keys(random_crop_result, target_keys)
assert check_crop(imgs, random_crop_result['imgs'],
results['crop_bbox'])
h, w = random_crop_result['img_shape']
assert h == w == 256