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classification speed #134
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With a Titan X Pascal, running crfasrnn_demo.py takes 0.4 seconds per image (500x500) in GPU mode. |
@bittnt thanks are you using crfasrnn_demo.py or a custom script? are you running on docker? |
you meant 500x500 ? |
500x500 is the image resolution. I was using crfasrnn_demo.py script. |
@bittnt |
@bittnt Finally I'm able to compile it and run the test successfully with cuda 7 and cudnn 3 only (all other up versions fail), but the speed is really low compare to yours (4.2 s) for the default image |
I have tested this under CUDA8, CUDA7.5, CUDA6.5, and CUDA6. |
@bittnt Great to know :) do you compile using CUDNN or not ? |
I am not sure what is the problem. The speed you reported sounds like running the whole FCN-8s+crfasrnn on CPU rather than GPUs. Also, check the version of the code you are using. I had tested the code on K80, both in AWS and Google Cloud before, it should take less than 1 second at least on the image with resolution 500x500. |
@bittnt Can you please tell which version of cuDNN you used with CUDA8 ? |
@akashdexati I think the error should be resolved if you use the crfasrnn branch (https://github.com/torrvision/caffe/tree/crfrnn) of the code rather than master. You do need to change the prototxt a bit for using the new branch. The new branch code merges the CRFasRNN layer with the latest Caffe, which supports CUDA8 and latest CUDNN. |
@bittnt |
@bittnt I worked on the |
Hello, while running crfasrnn_demo.py, i'm not able to go below 4s on a K80 or P100.
It's running on GPU I'm sure (I checked memory allocations).
Seems pretty slow to me, does anyone got any idea on how I could speed up the classification ? Thanks
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