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https://github.com/syoyo/visemenet-docker
Run VisnemeNet inference in nvidia-docker container
https://github.com/syoyo/visemenet-docker
Last synced: 18 days ago
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Run VisnemeNet inference in nvidia-docker container
- Host: GitHub
- URL: https://github.com/syoyo/visemenet-docker
- Owner: syoyo
- License: mit
- Created: 2019-02-20T05:11:57.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-02-20T05:20:30.000Z (almost 6 years ago)
- Last Synced: 2024-10-16T13:21:40.960Z (2 months ago)
- Language: Dockerfile
- Size: 1.95 KB
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Docker file for running VisemeNet inference.
It looks VisemeNet https://github.com/yzhou359/VisemeNet_tensorflow only runs in CUDA 8.0 environment, so I made a Docker file to run VisemeNet in CUDA 8.0 environment.
## Requirements
* Host: nvidia driver installed + CUDA 8 or 9(10 may work?)
* nvidia-docker2 https://github.com/NVIDIA/nvidia-dockerWe've confirmed Ubutu 16.06 + CUDA 9.2 works well for the host.
## Build docker image
Run `build.sh`
## Download VisemeNet
Clone VisemeNet somewhere and also download & store checkpoint files as described in VisemeNet's README.
```
$ https://github.com/yzhou359/VisemeNet_tensorflow.git
# Download checkpoint files and put it to VisemeNet_tensorflow/data/ckpt/pretrain_biwi/
```## Run VisemeNet in contaienr environment.
Setup audio.
Run docker in CUDA 8.0 environment. Bind host's VisemeNet directory to docker container.
Edit VisemeNet path `run.sh`, then
```
$ ./run.sh# cd /VisemeNet_tensorflow
# python3 main_test.py
````mayaparam_viseme.txt` will be generated in host's volume.
## License
MIT license.