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fix: don't reuse the same image over and over when resizing

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Former-commit-id: 182f0ed044dfebda406ee93a9a1071c7b37e2a2d [formerly 3f11f436feb764fe04c6b6b1ba41e2dcd4d6a986]
Former-commit-id: 81db41632a11963da271b24b1fd8b087aa2909af
This commit is contained in:
Laurent Fainsin 2022-08-25 16:21:23 +02:00
parent 5bd2e5b2c4
commit a876a741f0
2 changed files with 29 additions and 27 deletions
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2
src/notebooks/comp.ipynb.REMOVED.git-id
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@ -1 +1 @@
e7aad782356a06d40585b15274e7aeed664b2c03
c2144df415f2913c12a788aa8070ad538ce60480

54
src/utils/paste.py
View file

@ -49,43 +49,43 @@ class RandomPaste(A.DualTransform):
# paste spheres
for (x, y, shearx, sheary, shape, angle, brightness, contrast) in augmentations:
paste_img = T.functional.adjust_contrast(
paste_img_aug = T.functional.adjust_contrast(
paste_img,
contrast_factor=contrast,
)
paste_img = T.functional.adjust_brightness(
paste_img,
paste_img_aug = T.functional.adjust_brightness(
paste_img_aug,
brightness_factor=brightness,
)
paste_img = T.functional.affine(
paste_img,
paste_img_aug = T.functional.affine(
paste_img_aug,
scale=0.95,
angle=angle,
translate=(0, 0),
shear=(shearx, sheary),
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.BICUBIC,
)
paste_img = T.functional.resize(
paste_img,
paste_img_aug = T.functional.resize(
paste_img_aug,
size=shape,
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.LANCZOS,
)
paste_mask = T.functional.affine(
paste_mask_aug = T.functional.affine(
paste_mask,
scale=0.95,
angle=angle,
translate=(0, 0),
shear=(shearx, sheary),
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.BICUBIC,
)
paste_mask = T.functional.resize(
paste_mask,
paste_mask_aug = T.functional.resize(
paste_mask_aug,
size=shape,
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.LANCZOS,
)
img.paste(paste_img, (x, y), paste_mask)
img.paste(paste_img_aug, (x, y), paste_mask_aug)
return np.array(img.convert("RGB"))
@ -96,25 +96,25 @@ class RandomPaste(A.DualTransform):
# copy paste_img and paste_mask
paste_mask = paste_mask.copy()
for (x, y, shearx, sheary, shape, angle, _, _) in augmentations:
paste_mask = T.functional.affine(
for i, (x, y, shearx, sheary, shape, angle, _, _) in enumerate(augmentations):
paste_mask_aug = T.functional.affine(
paste_mask,
scale=0.95,
angle=angle,
translate=(0, 0),
shear=(shearx, sheary),
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.BICUBIC,
)
paste_mask = T.functional.resize(
paste_mask,
paste_mask_aug = T.functional.resize(
paste_mask_aug,
size=shape,
interpolation=T.InterpolationMode.BILINEAR,
interpolation=T.InterpolationMode.LANCZOS,
)
# binarize the mask -> {0, 1}
paste_mask_bin = paste_mask.point(lambda p: 1 if p > 10 else 0)
paste_mask_aug_bin = paste_mask_aug.point(lambda p: i + 1 if p > 10 else 0)
mask.paste(paste_mask, (x, y), paste_mask_bin)
mask.paste(paste_mask_aug, (x, y), paste_mask_aug_bin)
return np.array(mask.convert("L"))
@ -164,6 +164,8 @@ class RandomPaste(A.DualTransform):
augmentations.append((x, y, shearx, sheary, tuple(shape), angle, brightness, contrast))
ite += 1
params.update(
{
"augmentations": augmentations,
@ -175,8 +177,8 @@ class RandomPaste(A.DualTransform):
return params
@staticmethod
def overlap(positions, x1, y1, w, h):
for x2, y2, _, _, _, _, _, _ in positions:
if x1 + w >= x2 and x1 <= x2 + w and y1 + h >= y2 and y1 <= y2 + h:
def overlap(positions, x1, y1, w1, h1):
for x2, y2, _, _, (w2, h2), _, _, _ in positions:
if x1 + w1 >= x2 and x1 <= x2 + w2 and y1 + h1 >= y2 and y1 <= y2 + h2:
return True
return False