Add at new repo again

vton-api/preprocess/humanparsing/mhp_extension/detectron2/docker/Dockerfile

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+FROM nvidia/cuda:10.1-cudnn7-devel
+
+ENV DEBIAN_FRONTEND noninteractive
+RUN apt-get update && apt-get install -y \
+	python3-opencv ca-certificates python3-dev git wget sudo  \
+	cmake ninja-build protobuf-compiler libprotobuf-dev && \
+  rm -rf /var/lib/apt/lists/*
+RUN ln -sv /usr/bin/python3 /usr/bin/python
+
+# create a non-root user
+ARG USER_ID=1000
+RUN useradd -m --no-log-init --system  --uid ${USER_ID} appuser -g sudo
+RUN echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers
+USER appuser
+WORKDIR /home/appuser
+
+ENV PATH="/home/appuser/.local/bin:${PATH}"
+RUN wget https://bootstrap.pypa.io/get-pip.py && \
+	python3 get-pip.py --user && \
+	rm get-pip.py
+
+# install dependencies
+# See https://pytorch.org/ for other options if you use a different version of CUDA
+RUN pip install --user tensorboard cython
+RUN pip install --user torch==1.5+cu101 torchvision==0.6+cu101 -f https://download.pytorch.org/whl/torch_stable.html
+RUN pip install --user 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
+
+RUN pip install --user 'git+https://github.com/facebookresearch/fvcore'
+# install detectron2
+RUN git clone https://github.com/facebookresearch/detectron2 detectron2_repo
+# set FORCE_CUDA because during `docker build` cuda is not accessible
+ENV FORCE_CUDA="1"
+# This will by default build detectron2 for all common cuda architectures and take a lot more time,
+# because inside `docker build`, there is no way to tell which architecture will be used.
+ARG TORCH_CUDA_ARCH_LIST="Kepler;Kepler+Tesla;Maxwell;Maxwell+Tegra;Pascal;Volta;Turing"
+ENV TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST}"
+
+RUN pip install --user -e detectron2_repo
+
+# Set a fixed model cache directory.
+ENV FVCORE_CACHE="/tmp"
+WORKDIR /home/appuser/detectron2_repo
+
+# run detectron2 under user "appuser":
+# wget http://images.cocodataset.org/val2017/000000439715.jpg -O input.jpg
+# python3 demo/demo.py  \
+	#--config-file configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \
+	#--input input.jpg --output outputs/ \
+	#--opts MODEL.WEIGHTS detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl