updates
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@ -511,7 +511,7 @@ def load_image(self, index):
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img = cv2.imread(img_path) # BGR
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img = cv2.imread(img_path) # BGR
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assert img is not None, 'Image Not Found ' + img_path
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assert img is not None, 'Image Not Found ' + img_path
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r = self.img_size / max(img.shape) # size ratio
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r = self.img_size / max(img.shape) # size ratio
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if self.augment and r < 1.0: # if training (NOT testing), downsize to inference shape
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if self.augment: # if training (NOT testing), downsize to inference shape
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h, w, _ = img.shape
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h, w, _ = img.shape
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img = cv2.resize(img, (int(w * r), int(h * r)), interpolation=cv2.INTER_LINEAR) # _LINEAR fastest
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img = cv2.resize(img, (int(w * r), int(h * r)), interpolation=cv2.INTER_LINEAR) # _LINEAR fastest
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return img
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return img
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