YoloV5 way too less FPS (about 30fps), How can I improve it?-CodePudding

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I use yolov5s for game target detection, only 30fps.

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Although the target inference time is only 10ms, I found that it takes about 15 seconds to complete the detection of 500 images, 500/15=33.33, which is about 33fps.

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My gpu is 3070ti. This is the utilization rate during detection.

I have tried to change the version of pytorch and cuda, tried to use different weights, and tried to reduce the size of the detected image, but it didn't work.

CodePudding user response：

Because your GPU not fully loaded, probably you preprocessing take match time. Evaluate real yolov5 performance on you hardware with code like this:

import time 

dummy_frame = torch.randn(32,3,416,416).cuda() #dummy data
model.eval()
model.cuda()

start = time.time()
for i in range(10):
  out = model(dummy_frame)
time_spent = time.time() - start
fps = 10*32 / time_spent   # batches * batch_size
print(f"{fps:.2f} fps") # 344 FPS on T4 in colab

if fps on test significantly high then your current, try to improve your preprocessing pipeline