Open warmshao opened 1 month ago
amazing work congrats
amazing work congrats
thanks! The speed is truly unbelievably fast. Perhaps it can be used for some interesting applications.
I still need to compile onnxrruntime gpu myself, which is a bit discouraging
I still need to compile onnxrruntime gpu myself, which is a bit discouraging
The latest onnxruntime-gpu still doesn't support grid_sample cuda, so we need build it from source. But I will upload a docker image soon, stay tuned!
Very good, it runs at a steady 20FPS on RTX 3080 . 👍️
FasterLivePortrait.mp4
wow, cool! Are you using tensorrt or onnx?
Very good, it runs at a steady 20FPS on RTX 3080 . 👍️ cool
hi guys, I have uploaded an docker image that supports docker running https://github.com/warmshao/FasterLivePortrait. Please try it out. I will provide integration packages for Windows and macOS that support one-click run. Stay tuned.
Thanks, but not working
Could you share your Dockerfile so that I can build myself?
Thanks, but not working
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Could you share your Dockerfile so that I can build myself? You can try installing pycuda yourself: pip install pycuda. Actually, I follows the readme tutorial step by step to install in the container, then commit it, there's no Dockerfile.
nvidia-smi also failed so the image cannot be used, I must build from scratch
but I got a lot of compile error when follow the readme
seems some libraries version not compatible
nvidia-smi also failed so the image cannot be used, I must build from scratch but I got a lot of compile error when follow the readme seems some libraries version not compatible
pls refer this: https://github.com/warmshao/FasterLivePortrait/issues/8
Thanks, it works after fix libcuda.so.1 and libnvidia-ml.so.1 also need to fix scripts/all_onnx2trt.sh to retinaface_det_static.onnx and face_2dpose_106_static.onnx
3060 with official pytorch, source/s6.jpg + driving/d0.mp3: real 0m16.065s user 0m19.367s sys 0m1.738s
compiled model can speed up around 3s
TensortRT: real 0m7.773s user 0m11.793s sys 0m11.129s
Install-free, extract-and-play Windows package with TensorRT support now available! please refer FasterLivePortrait releases, Really fast and very convenient!!!
will this work to a video target ?
will this work to a video target ?
yes
My implementation: https://github.com/warmshao/FasterLivePortrait New Features: