Open bianxg opened 3 years ago
Can I optimizing trained model using openvino? Please refer the openvino's limit: https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers.html
You can give it a try and let me know how it goes.
I tried and met a error, please refer https://github.com/openvinotoolkit/openvino/issues/3846
Please refer the response on openvinotoolkit/openvino#3846 What should the input_shape be? Is [1,3,1080,1920] ok What's difference between the output pha_sm and pha? Thanks.
The input shape is correct if your image is 1920x1080 resolution.
pha
and fgr
are the actual output. pha_sm
is from the base network (You can refer to the architecture in the original research paper). It is only output for training.
There is a challenge to support If. Any ideas? https://github.com/openvinotoolkit/openvino/issues/2406
The input shape is correct if your image is 1920x1080 resolution.
pha
andfgr
are the actual output.pha_sm
is from the base network (You can refer to the architecture in the original research paper). It is only output for training.
Please refer : https://blog.csdn.net/lhyyhlfornew/article/details/109562383
Can you remove If operator by modifying squeeze() using index method like the blog's method? Or how can I do it? Thanks.
I see. The only place squeeze()
is used is in refiner.py
. You can change ref.squeeze(1)
in refiner.py
to ref[:, 0, :, :]
. Then re-export ONNX. This should get rid of the if node.
Hi,Does OpenVino accelerate only on Intel CPUs? Does it work for AMD?
Thanks for your awesome work! I hope to apply it on CPU. How can I optimize it for CPU ? Any suggestions? Thanks.