def test_flip_lazy(self):
with pytest.raises(ValueError):
Flip(direction='vertically', lazy=True)
target_keys = ['imgs', 'flip_direction', 'modality']
# do not flip imgs.
imgs = list(np.random.rand(2, 64, 64, 3))
imgs_tmp = imgs.copy()
results = dict(imgs=imgs_tmp, modality='RGB')
flip = Flip(flip_ratio=0, direction='horizontal', lazy=True)
flip_results = flip(results)
assert id(imgs_tmp) == id(flip_results['imgs'])
assert assert_dict_has_keys(flip_results, target_keys)
flip_results_fuse = Fuse()(flip_results)
assert np.equal(imgs, results['imgs']).all()
assert id(flip_results['imgs']) == id(results['imgs'])
assert flip_results_fuse['imgs'][0].shape == (64, 64, 3)
# always flip imgs horizontally.
imgs = list(np.random.rand(2, 64, 64, 3))
imgs_tmp = imgs.copy()
results = dict(imgs=imgs_tmp, modality='RGB')
flip = Flip(flip_ratio=1, direction='horizontal', lazy=True)
flip_results = flip(results)
assert id(imgs_tmp) == id(flip_results['imgs'])
assert assert_dict_has_keys(flip_results, target_keys)
flip_results_fuse = Fuse()(flip_results)
assert check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert flip_results_fuse['imgs'][0].shape == (64, 64, 3)
# always flip imgs vertivally.
imgs = list(np.random.rand(2, 64, 64, 3))
imgs_tmp = imgs.copy()
results = dict(imgs=imgs_tmp, modality='RGB')
flip = Flip(flip_ratio=1, direction='vertical', lazy=True)
flip_results = flip(results)
assert id(imgs_tmp) == id(flip_results['imgs'])
assert assert_dict_has_keys(flip_results, target_keys)
flip_results_fuse = Fuse()(flip_results)
assert check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert flip_results_fuse['imgs'][0].shape == (64, 64, 3)
assert repr(flip) == (f'{flip.__class__.__name__}'
f'(flip_ratio={1}, direction=vertical, '
f'flip_label_map={None}, lazy={True})')
def test_flip(self):
with pytest.raises(ValueError):
# direction must be in ['horizontal', 'vertical']
Flip(direction='vertically')
target_keys = ['imgs', 'flip_direction', 'modality']
# do not flip imgs.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
flip = Flip(flip_ratio=0, direction='horizontal')
flip_results = flip(results)
assert assert_dict_has_keys(flip_results, target_keys)
assert np.array_equal(imgs, results['imgs'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# always flip imgs horizontally.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
results['gt_bboxes'] = np.array([[0, 0, 60, 60]])
results['proposals'] = np.array([[0, 0, 60, 60]])
flip = Flip(flip_ratio=1, direction='horizontal')
flip_results = flip(results)
assert assert_dict_has_keys(flip_results, target_keys)
if flip_results['flip'] is True:
assert check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# flip flow images horizontally
imgs = [
np.arange(16).reshape(4, 4).astype(np.float32),
np.arange(16, 32).reshape(4, 4).astype(np.float32)
]
results = dict(imgs=copy.deepcopy(imgs), modality='Flow')
flip = Flip(flip_ratio=1, direction='horizontal')
flip_results = flip(results)
assert assert_dict_has_keys(flip_results, target_keys)
imgs = [x.reshape(4, 4, 1) for x in imgs]
flip_results['imgs'] = [
x.reshape(4, 4, 1) for x in flip_results['imgs']
]
if flip_results['flip'] is True:
assert check_flip([imgs[0]],
[mmcv.iminvert(flip_results['imgs'][0])],
flip_results['flip_direction'])
assert check_flip([imgs[1]], [flip_results['imgs'][1]],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# always flip imgs vertivally.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
flip = Flip(flip_ratio=1, direction='vertical')
flip_results = flip(results)
assert assert_dict_has_keys(flip_results, target_keys)
if flip_results['flip'] is True:
assert check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
assert repr(flip) == (f'{flip.__class__.__name__}'
f'(flip_ratio={1}, direction=vertical, '
f'flip_label_map={None}, lazy={False})')
# transform label for the flipped image with the specific label.
_flip_label_map = {4: 6}
imgs = list(np.random.rand(2, 64, 64, 3))
# the label should be mapped.
results = dict(imgs=copy.deepcopy(imgs), modality='RGB', label=4)
flip = Flip(flip_ratio=1,
direction='horizontal',
flip_label_map=_flip_label_map)
flip_results = flip(results)
assert results['label'] == 6
# the label should not be mapped.
results = dict(imgs=copy.deepcopy(imgs), modality='RGB', label=3)
flip = Flip(flip_ratio=1,
direction='horizontal',
flip_label_map=_flip_label_map)
flip_results = flip(results)
assert results['label'] == 3
def test_flip(self):
with pytest.raises(ValueError):
# direction must be in ['horizontal', 'vertical']
Flip(direction='vertically')
target_keys = ['imgs', 'flip_direction', 'modality']
# do not flip imgs.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
flip = Flip(flip_ratio=0, direction='horizontal')
flip_results = flip(results)
assert self.check_keys_contain(flip_results.keys(), target_keys)
assert np.array_equal(imgs, results['imgs'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# always flip imgs horizontally.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
flip = Flip(flip_ratio=1, direction='horizontal')
flip_results = flip(results)
assert self.check_keys_contain(flip_results.keys(), target_keys)
if flip_results['flip'] is True:
assert self.check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# flip flow images horizontally
imgs = [
np.arange(16).reshape(4, 4).astype(np.float32),
np.arange(16, 32).reshape(4, 4).astype(np.float32)
]
results = dict(imgs=copy.deepcopy(imgs), modality='Flow')
flip = Flip(flip_ratio=1, direction='horizontal')
flip_results = flip(results)
assert self.check_keys_contain(flip_results.keys(), target_keys)
imgs = [x.reshape(4, 4, 1) for x in imgs]
flip_results['imgs'] = [
x.reshape(4, 4, 1) for x in flip_results['imgs']
]
if flip_results['flip'] is True:
assert self.check_flip([imgs[0]],
[mmcv.iminvert(flip_results['imgs'][0])],
flip_results['flip_direction'])
assert self.check_flip([imgs[1]], [flip_results['imgs'][1]],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
# always flip imgs vertivally.
imgs = list(np.random.rand(2, 64, 64, 3))
results = dict(imgs=copy.deepcopy(imgs), modality='RGB')
flip = Flip(flip_ratio=1, direction='vertical')
flip_results = flip(results)
assert self.check_keys_contain(flip_results.keys(), target_keys)
if flip_results['flip'] is True:
assert self.check_flip(imgs, flip_results['imgs'],
flip_results['flip_direction'])
assert id(flip_results['imgs']) == id(results['imgs'])
assert np.shape(flip_results['imgs']) == np.shape(imgs)
assert repr(flip) == (f'{flip.__class__.__name__}'
f'(flip_ratio={1}, direction=vertical, '
f'lazy={False})')