updates
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+1
-1
@@ -74,7 +74,7 @@ class LoadImages: # for inference
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print('image %g/%g %s: ' % (self.count, self.nF, path), end='')
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# Padded resize
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img, _, _, _ = letterbox(img0, height=self.height)
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img, _, _, _ = letterbox_rect(img0, height=self.height)
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print('%gx%g ' % img.shape[:2], end='') # print image size
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# Normalize RGB
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+3
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@@ -102,13 +102,9 @@ def xywh2xyxy(x):
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def scale_coords(img1_shape, coords, img0_shape):
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# Rescale coords1 (xyxy) from img1_shape to img0_shape
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gain = img1_shape / max(img0_shape[:2]) # gain = old / new
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# pad_x = np.mod(img1_shape - img0_shape[1] * gain, 32) / 2 # width padding
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# pad_y = np.mod(img1_shape - img0_shape[0] * gain, 32) / 2 # height padding
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pad_x = (img1_shape - img0_shape[1] * gain) / 2 # width padding
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pad_y = (img1_shape - img0_shape[0] * gain) / 2 # height padding
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coords[:, [0, 2]] -= pad_x
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coords[:, [1, 3]] -= pad_y
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gain = max(img1_shape) / max(img0_shape) # gain = old / new
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coords[:, [0, 2]] -= (img1_shape[3] - img0_shape[1] * gain) / 2 # x padding
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coords[:, [1, 3]] -= (img1_shape[2] - img0_shape[0] * gain) / 2 # y padding
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coords[:, :4] /= gain
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coords[:, :4] = coords[:, :4].clamp(min=0)
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return coords
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