Update yolov8_det_trt.py
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@ -167,7 +167,7 @@ class YoLov8TRT(object):
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# Do postprocess
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for i in range(self.batch_size):
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result_boxes, result_scores, result_classid = self.post_process(
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output[i * 6001: (i + 1) * 6001], batch_origin_h[i], batch_origin_w[i]
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output[i * 38001: (i + 1) * 38001], batch_origin_h[i], batch_origin_w[i]
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)
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# Draw rectangles and labels on the original image
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for j in range(len(result_boxes)):
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@ -290,7 +290,7 @@ class YoLov8TRT(object):
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# Get the num of boxes detected
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num = int(output[0])
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# Reshape to a two dimentional ndarray
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pred = np.reshape(output[1:], (-1, 6))[:num, :]
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pred = np.reshape(output[1:], (-1, 38))[:num, :]
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# Do nms
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boxes = self.non_max_suppression(pred, origin_h, origin_w, conf_thres=CONF_THRESH, nms_thres=IOU_THRESHOLD)
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result_boxes = boxes[:, :4] if len(boxes) else np.array([])
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