Update dependencies for docker image

dockerfiles/runtime_ubt22/Dockerfile

@@ -0,0 +1,88 @@
+# Please build this dockerfile with nvidia-container-runtime
+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
+
+# Install apt packages
+RUN apt-get update && \
+    apt-get install -y \
+        wget git vim \
+        make \
+        libblas-dev liblapack-dev libatlas-base-dev\
+    && \
+    apt-get autoclean
+
+# Install miniconda
+RUN wget -q \
+    https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+    && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/miniconda \
+    && rm -f Miniconda3-latest-Linux-x86_64.sh
+
+# Update in bashrc
+RUN echo "source /opt/miniconda/etc/profile.d/conda.sh" >> /root/.bashrc && \
+    echo "conda deactivate" >> /root/.bashrc
+
+# Prepare python env
+ARG PY_VER
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda create -n openxrlab python=$PY_VER -y && \
+    conda activate openxrlab && \
+    conda install ffmpeg -y && \
+    conda clean -y --all
+
+# Prepare pytorch env
+ARG CUDA_VER
+ARG TORCH_VER
+ARG TORCHV_VER
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    conda install pytorch==$TORCH_VER torchvision==$TORCHV_VER pytorch-cuda=$CUDA_VER cudatoolkit=$CUDA_VER -c pytorch -c nvidia -y && \
+    conda clean -y --all
+
+# Prepare pytorch3d env
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    conda install -c fvcore -c iopath -c conda-forge fvcore iopath && \
+    conda install -c bottler nvidiacub && \
+    conda install pytorch3d -c pytorch3d && \
+    conda clean -y --all
+
+# Prepare pip env
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip install pre-commit interrogate coverage pytest && \
+    pip install xrprimer && \
+    pip cache purge
+
+# Install build requirements
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip install -r https://raw.githubusercontent.com/openxrlab/xrmocap/main/requirements/build.txt && \
+    pip cache purge
+
+# Install test requirements
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip install -r https://raw.githubusercontent.com/openxrlab/xrmocap/main/requirements/test.txt && \
+    pip cache purge
+
+# Install mmhuman3d
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    cd /opt && \
+    git clone https://github.com/open-mmlab/mmhuman3d.git && \
+    cd mmhuman3d && pip install -e . && \
+    pip cache purge
+
+# Re-install numpy+scipy for mm-repos and smplx
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip uninstall scipy numpy -y && \
+    pip install numpy==1.23.5 scipy==1.10.0 && \
+    pip cache purge
+
+# Re-install opencv for headless system
+# For cudagl base image, please remove both and re-install opencv-python
+RUN . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip uninstall opencv-python opencv-python-headless -y && \
+    pip install opencv-python-headless && \
+    pip cache purge

dockerfiles/runtime_ubt22/build_runtime_docker.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+CUDA_VER=11.8
+PY_VER=3.10
+MMCV_VER=1.7.0
+TORCH_VER=2.0.1
+TORCHV_VER=0.15.2
+CUDA_VER_DIGIT=${CUDA_VER//./}
+PY_VER_DIGIT=${PY_VER//./}
+MMCV_VER_DIGIT=${MMCV_VER//./}
+TORCH_VER_DIGIT=${TORCH_VER//./}
+FINAL_TAG="openxrlab/xrmocap_runtime:ubuntu2204_x64_cuda${CUDA_VER_DIGIT}_py${PY_VER_DIGIT}_torch${TORCH_VER_DIGIT}_mmcv${MMCV_VER_DIGIT}"
+echo "tag to build: $FINAL_TAG"
+BUILD_ARGS="--build-arg CUDA_VER=${CUDA_VER} --build-arg PY_VER=${PY_VER} --build-arg MMCV_VER=${MMCV_VER} --build-arg TORCH_VER=${TORCH_VER} --build-arg TORCHV_VER=${TORCHV_VER}"
+# build according to Dockerfile
+TAG=${FINAL_TAG}_not_compatible
+docker build -t $TAG -f dockerfiles/runtime_ubt18/Dockerfile $BUILD_ARGS --progress=plain .
+# Install mpr and mmcv-full with GPU
+CONTAINER_ID=$(docker run -it --gpus all -d $TAG)
+docker exec -ti $CONTAINER_ID sh -c "
+    . /opt/miniconda/etc/profile.d/conda.sh && \
+    conda activate openxrlab && \
+    pip install -U openmim && \
+    mim install mmcv-full==${MMCV_VER} && \    
+    pip install git+https://github.com/rmbashirov/minimal_pytorch_rasterizer.git && \
+    pip cache purge
+"
+docker commit $CONTAINER_ID $FINAL_TAG
+docker rm -f $CONTAINER_ID
+docker rmi $TAG
+echo "Successfully tagged $FINAL_TAG"

docs/en/installation.md

@@ -223,7 +223,7 @@ We provide a Dockerfile to build a runtime image. Ensure that you are using [doc
 Or pull a built image from docker hub.
 
 ```shell
-docker pull openxrlab/xrmocap_runtime:ubuntu1804_x64_cuda116_py38_torch1121_mmcv161
+docker pull openxrlab/xrmocap_runtime:ubuntu2204_x64_cuda118_py310_torch201_mmcv170
 ```
 
 Run it with:

scripts/run_docker.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-TAG="openxrlab/xrmocap_runtime:ubuntu1804_x64_cuda116_py38_torch1121_mmcv161"
+TAG="openxrlab/xrmocap_runtime:ubuntu2204_x64_cuda118_py310_torch201_mmcv170"
 # modify data mount below
 VOLUMES="-v $PWD:/workspace/xrmocap -v /data:/workspace/xrmocap/data"
 WORKDIR="-w /workspace/xrmocap"