def test_lambda_transform():
def negate_image(image, **kwargs):
return -image
def one_hot_mask(mask, num_channels, **kwargs):
new_mask = np.eye(num_channels, dtype=np.uint8)[mask]
return new_mask
def vflip_bbox(bbox, **kwargs):
return F.bbox_vflip(bbox, **kwargs)
def vflip_keypoint(keypoint, **kwargs):
return F.keypoint_vflip(keypoint, **kwargs)
aug = A.Lambda(image=negate_image,
mask=partial(one_hot_mask, num_channels=16),
bbox=vflip_bbox,
keypoint=vflip_keypoint,
p=1)
output = aug(
image=np.ones((10, 10, 3), dtype=np.float32),
mask=np.tile(np.arange(0, 10), (10, 1)),
bboxes=[(10, 15, 25, 35)],
keypoints=[(20, 30, 40, 50)],
)
assert (output["image"] < 0).all()
assert output["mask"].shape[2] == 16 # num_channels
assert output["bboxes"] == [F.bbox_vflip((10, 15, 25, 35), 10, 10)]
assert output["keypoints"] == [F.keypoint_vflip((20, 30, 40, 50), 10, 10)]
def vflip_bbox(bbox, **kwargs):
return F.bbox_vflip(bbox, **kwargs)
def test_bbox_vflip():
assert F.bbox_vflip((0.1, 0.2, 0.6, 0.5), 100, 200) == (0.1, 0.5, 0.6, 0.8)
def test_bbox_vflip():
assert F.bbox_vflip((0.1, 0.2, 0.6, 0.5), 100, 200) == (0.1, 0.5, 0.6, 0.8)
def test_bbox_hflip():
assert F.bbox_hflip((0.1, 0.2, 0.6, 0.5), 100, 200) == (0.4, 0.2, 0.9, 0.5)
@pytest.mark.parametrize(
["code", "func"],
[
[0, F.bbox_vflip],
[1, F.bbox_hflip],
[
-1, lambda bbox, rows, cols: F.bbox_vflip(
F.bbox_hflip(bbox, rows, cols), rows, cols)
],
],
)
def test_bbox_flip(code, func):
rows, cols = 100, 200
bbox = [0.1, 0.2, 0.6, 0.5]
assert F.bbox_flip(bbox, code, rows, cols) == func(bbox, rows, cols)
def test_crop_bbox_by_coords():
cropped_bbox = A.crop_bbox_by_coords((0.5, 0.2, 0.9, 0.7),
(18, 18, 82, 82), 64, 64, 100, 100)
assert cropped_bbox == (0.5, 0.03125, 1.125, 0.8125)
def test_bbox_vflip(bbox, expected_output, input_type):
bbox = input_type(bbox)
flipped_bbox = F.bbox_vflip(bbox, cols=200, rows=100)
assert isinstance(flipped_bbox, tuple)
assert np.array_equal(flipped_bbox, expected_output)
def test_bbox_vflip():
assert F.bbox_vflip([0.1, 0.2, 0.6, 0.5], 100, 200) == [0.1, 0.5, 0.6, 0.8]
def test_bbox_vflip(bbox, expected_output, input_type):
bbox = input_type(bbox)
flipped_bbox = F.bbox_vflip(bbox, cols=200, rows=100)
assert isinstance(flipped_bbox, tuple)
assert np.array_equal(flipped_bbox, expected_output)
