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@ -29,16 +29,16 @@ pip install "git+https://github.com/facebookresearch/pytorch3d.git"
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pip install tensorflow-gpu==2.8.0
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pip install --upgrade "protobuf<=3.20.1"
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```
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如果用pytorch2.1，torchvision用0.16（可以去[torchvision官网](https://github.com/pytorch/vision)根据pytorch版本找匹配的）,cudatoolkit可以不用装
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安装常见问题[FAQ](/assets/faq.md)
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如果cuda为其他版本，上<https://pytorch.org/get-started/previous-versions/>安装相应版本的pytorch
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安装常见问题[FAQ](https://livetalking-doc.readthedocs.io/en/latest/faq.html)
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linux cuda环境搭建可以参考这篇文章 https://zhuanlan.zhihu.com/p/674972886
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## 2. Quick Start
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默认采用ernerf模型，webrtc推流到srs
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### 2.1 运行srs
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```
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export CANDIDATE='<服务器外网ip>'
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```bash
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export CANDIDATE='<服务器外网ip>' #如果srs与livetalking在同一层级内网，不需要执行这步
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docker run --rm --env CANDIDATE=$CANDIDATE \
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-p 1935:1935 -p 8080:8080 -p 1985:1985 -p 8000:8000/udp \
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registry.cn-hangzhou.aliyuncs.com/ossrs/srs:5 \
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@ -70,10 +70,10 @@ docker run --gpus all -it --network=host --rm registry.cn-beijing.aliyuncs.com/c
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代码在/root/metahuman-stream，先git pull拉一下最新代码，然后执行命令同第2、3步
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提供如下镜像
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- ucloud镜像: <https://www.compshare.cn/images-detail?ImageID=compshareImage-14pa8x8ucwr9&ImageType=Community&ytag=cs_lipku_image>
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推荐用该镜像，可以开放任意端口，不需要单独运行srs服务.
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- autodl镜像: <https://www.codewithgpu.com/i/lipku/metahuman-stream/base>
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[autodl教程](autodl/README.md)
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- ucloud镜像: <https://www.compshare.cn/images-detail?ImageID=compshareImage-14pa8x8ucwr9&ImageType=Community&ytag=cs_lipku_image>
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可以开放任意端口，不需要单独运行srs服务.
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## 5. 性能分析
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lipku
8 months ago