def post_process()

in models/01_YoloV5/01_Pytorch/processing.py [0:0]

• 15 lines of code
• 4 McCabe index (conditional complexity)

    def post_process(self, predictions, source_image_shape, image=None):
        xc = predictions[..., 4] > self.threshold
        predictions = predictions[xc]
        bboxes, scores, cids = self.get_detections(predictions)
        
        # Normalise box coordinates to be in the range (0, 1]
        h, w = source_image_shape[:2]
        h1, w1 = h, w
        if self.keep_ratio and h != w:
            # Padding was used during pre-process to make the source image square
            h1 = w1 = max(h, w)
            
        y_scale,x_scale = (h1,w1) / self.input_shape.astype(np.float32) / (h,w)
        bboxes[:, (0, 2)] *= x_scale
        bboxes[:, (1, 3)] *= y_scale
        bboxes = np.clip(bboxes, 0, 1)
        
        if image is not None:
            self.draw_cv2(image, bboxes, scores, cids)

        return (bboxes, scores, cids), image