Comments (2)
laisimiao
commented on August 20, 2024
BTW, its GPU usage is not so tight as cpu usage
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conquerhuang
commented on August 20, 2024
Different from other implementation on Siamese trackers. This demo directly crop trian image in original GOT10K dataset rather than crop the whole dataset before train. So during the train process, there will be a big burden on CPU. I have tried this demo on I7 9700k CPU RTX2080Ti GPU, it will taken 100% usage of CPU while token no more than 5% usage of GPU. If you don't have a powerful CPU and large RAM, I strongly recommend you to crop the training datasets for the first time.
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Related Issues (20)
- more details about requirements.txt HOT 1
- Hanning Window
- 安装menpo的OpenCV：failed HOT 1
- tset on vot2018 HOT 1
- 训练问题
- 运行demo.py问题 HOT 1
- got10K训练到一半时报错 HOT 2
- 运行train.py出错
- train
- RuntimeError: cuDNN error: CUDNN_STATUS_EXECUTION_FAILED
- raw results on Lasot benchmark
- siamfc.py中关于box坐标的问题 HOT 2
- can't test on vot
- test vot2018 AttributeError: shape HOT 1
- Please ask what datasets the pre-trained model was built on
- Validation loss doesn't decrease（驗證 loss 不會下降）
- Question about torch version
- Train on my own data set
- so what's the differences between test.py and demo.py
- the performance of got10k
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