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for result in results: preds = {} xmin, ymin, xmax, ymax = result["bbox"].astype("int") crop_img = img[ymin:ymax, xmin:xmax, :].copy() start = time.time() #特征识别 rec_results = self.rec_predictor.predict(crop_img) end = time.time() print('rec_predictor.predict程序运行时间为:', end - start, '秒')
这个问题怎么解决,我知道调整 threshold,max_det_results参数可以控制输出数量,这对检测结果有些什么影响呢, 除了调整参数外能否将识别部分用c++实现,或者有更高明的方式 rec_predictor.predict程序运行时间为: 0.2493739128112793 秒 Searcher.search程序运行时间为: 0.0 秒 rec_predictor.predict程序运行时间为: 0.21487092971801758 秒
rec_predictor.predict这个数量是max_det_results决定的,我看通常是设置的5,这样好像计算要达到1秒了=5*0,2(估算)
The text was updated successfully, but these errors were encountered:
这个位置如果想加速的话,就需要对这个for循环进行修改,比如改成并行或者组batch等操作,但我们目前没有计划支持哈,需要自己修改一下代码。对于max_det results,不建议调小,会漏掉一些检测框,影响精度
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cuicheng01
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这个问题怎么解决,我知道调整
threshold,max_det_results参数可以控制输出数量,这对检测结果有些什么影响呢, 除了调整参数外能否将识别部分用c++实现,或者有更高明的方式
rec_predictor.predict程序运行时间为: 0.2493739128112793 秒
Searcher.search程序运行时间为: 0.0 秒
rec_predictor.predict程序运行时间为: 0.21487092971801758 秒
rec_predictor.predict这个数量是max_det_results决定的,我看通常是设置的5,这样好像计算要达到1秒了=5*0,2(估算)
The text was updated successfully, but these errors were encountered: