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Support matrix=None case for piecewise affine #1495

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Nov 5, 2023
Merged

Support matrix=None case for piecewise affine #1495

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461b7a8
Support matrix=None case for piecewise affine
Dipet Nov 5, 2023
8529561
Regen jitter if check any positive is not valid
Dipet Nov 5, 2023
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12 changes: 9 additions & 3 deletions albumentations/augmentations/geometric/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -690,11 +690,13 @@ def keypoint_safe_rotate(
@clipped
def piecewise_affine(
img: np.ndarray,
matrix: skimage.transform.PiecewiseAffineTransform,
matrix: Optional[skimage.transform.PiecewiseAffineTransform],
interpolation: int,
mode: str,
cval: float,
) -> np.ndarray:
if matrix is None:
return img
return skimage.transform.warp(
img, matrix, order=interpolation, mode=mode, cval=cval, preserve_range=True, output_shape=img.shape
)
Expand Down Expand Up @@ -823,11 +825,13 @@ def from_distance_maps(

def keypoint_piecewise_affine(
keypoint: KeypointInternalType,
matrix: skimage.transform.PiecewiseAffineTransform,
matrix: Optional[skimage.transform.PiecewiseAffineTransform],
h: int,
w: int,
keypoints_threshold: float,
) -> KeypointInternalType:
if matrix is None:
return keypoint
x, y, a, s = keypoint[:4]
dist_maps = to_distance_maps([(x, y)], h, w, True)
dist_maps = piecewise_affine(dist_maps, matrix, 0, "constant", 0)
Expand All @@ -837,11 +841,13 @@ def keypoint_piecewise_affine(

def bbox_piecewise_affine(
bbox: BoxInternalType,
matrix: skimage.transform.PiecewiseAffineTransform,
matrix: Optional[skimage.transform.PiecewiseAffineTransform],
h: int,
w: int,
keypoints_threshold: float,
) -> BoxInternalType:
if matrix is None:
return bbox
x1, y1, x2, y2 = denormalize_bbox(bbox, h, w)[:4]
keypoints = [
(x1, y1),
Expand Down
17 changes: 12 additions & 5 deletions albumentations/augmentations/geometric/transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -908,7 +908,12 @@ def get_params_dependent_on_targets(self, params) -> dict:

jitter: np.ndarray = random_utils.normal(0, scale, (nb_cells, 2))
if not np.any(jitter > 0):
return {"matrix": None}
for i in range(10): # See: https://github.com/albumentations-team/albumentations/issues/1442
jitter = random_utils.normal(0, scale, (nb_cells, 2))
if np.any(jitter > 0):
break
if not np.any(jitter > 0):
return {"matrix": None}

y = np.linspace(0, h, nb_rows)
x = np.linspace(0, w, nb_cols)
Expand Down Expand Up @@ -944,11 +949,13 @@ def get_params_dependent_on_targets(self, params) -> dict:
"matrix": matrix,
}

def apply(self, img: np.ndarray, matrix: skimage.transform.PiecewiseAffineTransform = None, **params) -> np.ndarray:
def apply(
self, img: np.ndarray, matrix: Optional[skimage.transform.PiecewiseAffineTransform] = None, **params
) -> np.ndarray:
return F.piecewise_affine(img, matrix, self.interpolation, self.mode, self.cval)

def apply_to_mask(
self, img: np.ndarray, matrix: skimage.transform.PiecewiseAffineTransform = None, **params
self, img: np.ndarray, matrix: Optional[skimage.transform.PiecewiseAffineTransform] = None, **params
) -> np.ndarray:
return F.piecewise_affine(img, matrix, self.mask_interpolation, self.mode, self.cval_mask)

Expand All @@ -957,7 +964,7 @@ def apply_to_bbox(
bbox: BoxInternalType,
rows: int = 0,
cols: int = 0,
matrix: skimage.transform.PiecewiseAffineTransform = None,
matrix: Optional[skimage.transform.PiecewiseAffineTransform] = None,
**params
) -> BoxInternalType:
return F.bbox_piecewise_affine(bbox, matrix, rows, cols, self.keypoints_threshold)
Expand All @@ -967,7 +974,7 @@ def apply_to_keypoint(
keypoint: KeypointInternalType,
rows: int = 0,
cols: int = 0,
matrix: skimage.transform.PiecewiseAffineTransform = None,
matrix: Optional[skimage.transform.PiecewiseAffineTransform] = None,
**params
):
return F.keypoint_piecewise_affine(keypoint, matrix, rows, cols, self.keypoints_threshold)
Expand Down
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