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@@ -632,17 +632,18 @@ def load_image(self, index): |
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def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5): |
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r = np.random.uniform(-1, 1, 3) * [hgain, sgain, vgain] + 1 # random gains |
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hue, sat, val = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV)) |
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dtype = img.dtype # uint8 |
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x = np.arange(0, 256, dtype=r.dtype) |
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lut_hue = ((x * r[0]) % 180).astype(dtype) |
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lut_sat = np.clip(x * r[1], 0, 255).astype(dtype) |
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lut_val = np.clip(x * r[2], 0, 255).astype(dtype) |
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img_hsv = cv2.merge((cv2.LUT(hue, lut_hue), cv2.LUT(sat, lut_sat), cv2.LUT(val, lut_val))) |
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cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) # no return needed |
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if hgain or sgain or vgain: |
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r = np.random.uniform(-1, 1, 3) * [hgain, sgain, vgain] + 1 # random gains |
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hue, sat, val = cv2.split(cv2.cvtColor(img, cv2.COLOR_BGR2HSV)) |
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dtype = img.dtype # uint8 |
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x = np.arange(0, 256, dtype=r.dtype) |
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lut_hue = ((x * r[0]) % 180).astype(dtype) |
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lut_sat = np.clip(x * r[1], 0, 255).astype(dtype) |
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lut_val = np.clip(x * r[2], 0, 255).astype(dtype) |
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img_hsv = cv2.merge((cv2.LUT(hue, lut_hue), cv2.LUT(sat, lut_sat), cv2.LUT(val, lut_val))) |
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cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR, dst=img) # no return needed |
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def hist_equalize(img, clahe=True, bgr=False): |