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https://github.com/Laurent2916/REVA-QCAV.git
synced 2024-11-09 23:12:05 +00:00
fix: don't reuse the same image over and over when resizing
Former-commit-id: 182f0ed044dfebda406ee93a9a1071c7b37e2a2d [formerly 3f11f436feb764fe04c6b6b1ba41e2dcd4d6a986] Former-commit-id: 81db41632a11963da271b24b1fd8b087aa2909af
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parent
5bd2e5b2c4
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@ -1 +1 @@
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e7aad782356a06d40585b15274e7aeed664b2c03
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c2144df415f2913c12a788aa8070ad538ce60480
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@ -49,43 +49,43 @@ class RandomPaste(A.DualTransform):
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# paste spheres
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# paste spheres
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for (x, y, shearx, sheary, shape, angle, brightness, contrast) in augmentations:
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for (x, y, shearx, sheary, shape, angle, brightness, contrast) in augmentations:
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paste_img = T.functional.adjust_contrast(
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paste_img_aug = T.functional.adjust_contrast(
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paste_img,
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paste_img,
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contrast_factor=contrast,
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contrast_factor=contrast,
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)
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)
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paste_img = T.functional.adjust_brightness(
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paste_img_aug = T.functional.adjust_brightness(
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paste_img,
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paste_img_aug,
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brightness_factor=brightness,
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brightness_factor=brightness,
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)
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)
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paste_img = T.functional.affine(
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paste_img_aug = T.functional.affine(
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paste_img,
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paste_img_aug,
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scale=0.95,
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scale=0.95,
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angle=angle,
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angle=angle,
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translate=(0, 0),
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translate=(0, 0),
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shear=(shearx, sheary),
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shear=(shearx, sheary),
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.BICUBIC,
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)
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)
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paste_img = T.functional.resize(
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paste_img_aug = T.functional.resize(
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paste_img,
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paste_img_aug,
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size=shape,
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size=shape,
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.LANCZOS,
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)
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)
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paste_mask = T.functional.affine(
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paste_mask_aug = T.functional.affine(
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paste_mask,
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paste_mask,
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scale=0.95,
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scale=0.95,
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angle=angle,
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angle=angle,
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translate=(0, 0),
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translate=(0, 0),
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shear=(shearx, sheary),
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shear=(shearx, sheary),
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.BICUBIC,
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)
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)
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paste_mask = T.functional.resize(
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paste_mask_aug = T.functional.resize(
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paste_mask,
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paste_mask_aug,
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size=shape,
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size=shape,
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.LANCZOS,
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)
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)
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img.paste(paste_img, (x, y), paste_mask)
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img.paste(paste_img_aug, (x, y), paste_mask_aug)
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return np.array(img.convert("RGB"))
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return np.array(img.convert("RGB"))
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@ -96,25 +96,25 @@ class RandomPaste(A.DualTransform):
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# copy paste_img and paste_mask
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# copy paste_img and paste_mask
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paste_mask = paste_mask.copy()
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paste_mask = paste_mask.copy()
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for (x, y, shearx, sheary, shape, angle, _, _) in augmentations:
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for i, (x, y, shearx, sheary, shape, angle, _, _) in enumerate(augmentations):
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paste_mask = T.functional.affine(
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paste_mask_aug = T.functional.affine(
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paste_mask,
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paste_mask,
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scale=0.95,
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scale=0.95,
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angle=angle,
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angle=angle,
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translate=(0, 0),
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translate=(0, 0),
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shear=(shearx, sheary),
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shear=(shearx, sheary),
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.BICUBIC,
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)
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)
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paste_mask = T.functional.resize(
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paste_mask_aug = T.functional.resize(
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paste_mask,
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paste_mask_aug,
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size=shape,
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size=shape,
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interpolation=T.InterpolationMode.BILINEAR,
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interpolation=T.InterpolationMode.LANCZOS,
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)
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)
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# binarize the mask -> {0, 1}
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# binarize the mask -> {0, 1}
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paste_mask_bin = paste_mask.point(lambda p: 1 if p > 10 else 0)
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paste_mask_aug_bin = paste_mask_aug.point(lambda p: i + 1 if p > 10 else 0)
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mask.paste(paste_mask, (x, y), paste_mask_bin)
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mask.paste(paste_mask_aug, (x, y), paste_mask_aug_bin)
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return np.array(mask.convert("L"))
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return np.array(mask.convert("L"))
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@ -164,6 +164,8 @@ class RandomPaste(A.DualTransform):
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augmentations.append((x, y, shearx, sheary, tuple(shape), angle, brightness, contrast))
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augmentations.append((x, y, shearx, sheary, tuple(shape), angle, brightness, contrast))
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ite += 1
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params.update(
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params.update(
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{
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{
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"augmentations": augmentations,
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"augmentations": augmentations,
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@ -175,8 +177,8 @@ class RandomPaste(A.DualTransform):
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return params
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return params
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@staticmethod
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@staticmethod
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def overlap(positions, x1, y1, w, h):
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def overlap(positions, x1, y1, w1, h1):
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for x2, y2, _, _, _, _, _, _ in positions:
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for x2, y2, _, _, (w2, h2), _, _, _ in positions:
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if x1 + w >= x2 and x1 <= x2 + w and y1 + h >= y2 and y1 <= y2 + h:
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if x1 + w1 >= x2 and x1 <= x2 + w2 and y1 + h1 >= y2 and y1 <= y2 + h2:
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return True
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return True
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return False
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return False
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