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															@@ -75,25 +75,7 @@ def filtered(obj, objects_to_track, object_filters): 
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															 def create_tensor_input(frame, model_shape, region): 
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															 def create_tensor_input(frame, model_shape, region): 
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															-    # TODO: is it faster to just convert grayscale to RGB? or repeat dimensions with numpy? 
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															-    height = frame.shape[0] // 3 * 2 
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															-    width = frame.shape[1] 
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															-    # get the crop box if the region extends beyond the frame 
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															-    crop_x1 = max(0, region[0]) 
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															-    crop_y1 = max(0, region[1]) 
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															-    crop_x2 = min(width, region[2]) 
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															-    crop_y2 = min(height, region[3]) 
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															-    size = region[3] - region[1] 
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															-    cropped_frame = np.zeros((size, size), np.uint8) 
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															-    cropped_frame[ 
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															-        0 : crop_y2 - crop_y1, 
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															-        0 : crop_x2 - crop_x1, 
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															-    ] = frame[crop_y1:crop_y2, crop_x1:crop_x2] 
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															-    cropped_frame = np.repeat(np.expand_dims(cropped_frame, -1), 3, 2) 
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															+    cropped_frame = yuv_region_2_rgb(frame, region) 
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															     # Resize to 300x300 if needed 
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															     # Resize to 300x300 if needed 
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															     if cropped_frame.shape != (model_shape[0], model_shape[1], 3): 
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															     if cropped_frame.shape != (model_shape[0], model_shape[1], 3): 
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