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cfzd avatar cfzd commented on June 5, 2024 4

@liluxing153
一般来说，网络的推理速度指的是神经网络跑完一次forward的速度，也就是上面

with torch.no_grad():
    pred = net(img)

这一句的时间，按照你的速度应该也有200FPS，这个是比较通用的做法。

那为什么图像预处理或者后处理的时间不算呢？这主要是因为在真实的系统中，相机采集的数据是直接在内存中的，后端的网络输入是可以直接对接内存中的相机数据的，所以你在img_transforms中从硬盘读取的时间、转换成RGB的时间、归一化的时间、再把它挪到cuda内存上等等的时间都是不存在的。

那么后处理呢？其实你观察后处理的代码就可以发现核心的逻辑就是一个softmax再加上一个乘法求期望，这点计算量相比于神经网络的计算量九牛一毛，为什么还会比网络推理慢呢？这主要是由于为了方便用python的循环实现的，如果真正部署换成其他的方式，这点计算量是几乎没有延迟的。

综上，计算网络速度是看的网络推理速度，这也是一般的通用做法。

from ultra-fast-lane-detection-v2.

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