jeonghyo.k
3946ff6a25
- prediction/image/ FastAPI 서버 Docker 환경 구성 - Dockerfile: PyTorch 2.1 + CUDA 12.1 기반 GPU 이미지 - docker-compose.yml: GPU 할당 + 데이터 볼륨 마운트 - requirements.txt: 서버 의존성 목록 - .env.example: 환경변수 템플릿 - DOCKER_USAGE.md: 빌드/실행/API 사용법 문서 - Dockerfile에 .dockerignore 제외 폴더 mkdir -p 추가 - .gitignore: prediction/image 결과물 및 모델 가중치(.pth) 제외 추가 - dbInsert_csv.py, dbInsert_shp.py 삭제 (미사용 DB 로직) - api.py: dbInsert import 및 주석 처리된 DB 호출 코드 제거 - aerialRouter.ts: req.params 타입 오류 수정
50 lines
1.3 KiB
Docker
50 lines
1.3 KiB
Docker
ARG PYTORCH="1.11.0"
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ARG CUDA="11.3"
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ARG CUDNN="8"
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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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ARG MMCV="1.5.0"
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ARG MMSEG="0.25.0"
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ENV PYTHONUNBUFFERED TRUE
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RUN apt-get update && \
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DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y \
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ca-certificates \
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g++ \
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openjdk-11-jre-headless \
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# MMDet Requirements
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ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
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&& rm -rf /var/lib/apt/lists/*
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ENV PATH="/opt/conda/bin:$PATH"
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RUN export FORCE_CUDA=1
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# TORCHSEVER
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RUN pip install torchserve torch-model-archiver
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# MMLAB
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ARG PYTORCH
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ARG CUDA
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RUN ["/bin/bash", "-c", "pip install mmcv-full==${MMCV} -f https://download.openmmlab.com/mmcv/dist/cu${CUDA//./}/torch${PYTORCH}/index.html"]
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RUN pip install mmsegmentation==${MMSEG}
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RUN useradd -m model-server \
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&& mkdir -p /home/model-server/tmp
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COPY entrypoint.sh /usr/local/bin/entrypoint.sh
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RUN chmod +x /usr/local/bin/entrypoint.sh \
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&& chown -R model-server /home/model-server
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COPY config.properties /home/model-server/config.properties
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RUN mkdir /home/model-server/model-store && chown -R model-server /home/model-server/model-store
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EXPOSE 8080 8081 8082
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USER model-server
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WORKDIR /home/model-server
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ENV TEMP=/home/model-server/tmp
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ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
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CMD ["serve"]
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