Dockerfile for same one wants to use this repo on docker😉

[Ozora Ogino]

ARG PYTORCH="1.8.1"
ARG CUDA="10.2"
ARG CUDNN="7"

FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel

ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0+PTX"
ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"

# To fix GPG key error when running apt-get update
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub

RUN apt-get update && apt-get install -y git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx\
	&& apt-get clean \
	&& rm -rf /var/lib/apt/lists/*

RUN git clone https://github.com/cfzd/Ultra-Fast-Lane-Detection-V2 /lane
WORKDIR /lane
RUN pip3 install -r requirements.txt
RUN pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist --upgrade nvidia-dali-cuda110
WORKDIR /workspace