Dockerfile

#
# Dockerfile to build the image of the tiny_yolov2_onnx_cam application
#

ARG BASE_IMAGE=nvcr.io/nvidia/l4t-base:r32.5.0
FROM ${BASE_IMAGE}

ARG REPOSITORY_NAME=tiny_yolov2_onnx_cam
#ARG MODEL_URL='https://github.com/onnx/models/raw/master/vision/object_detection_segmentation/tiny-yolov2/model/tinyyolov2-8.tar.gz'
ARG MODEL_URL='https://github.com/onnx/models/raw/main/vision/object_detection_segmentation/tiny-yolov2/model/tinyyolov2-8.tar.gz'
ARG LABEL_URL='https://raw.githubusercontent.com/pjreddie/darknet/master/data/voc.names'

ENV DEBIAN_FRONTEND=noninteractive
ENV LANG C.UTF-8
ENV PATH="/usr/local/cuda/bin:${PATH}"
ENV LD_LIBRARY_PATH="/usr/local/cuda/lib64:${LD_LIBRARY_PATH}"

WORKDIR /tmp

RUN apt-get update && apt-get install -y ca-certificates
COPY  nvidia-l4t-apt-source.list /etc/apt/sources.list.d/nvidia-l4t-apt-source.list
COPY  jetson-ota-public.asc /etc/apt/trusted.gpg.d/jetson-ota-public.asc
RUN apt-get update

RUN apt-get update && \
    apt-get install -y libopencv-python && \
    apt-get install -y --no-install-recommends \
        python3-pip \
        python3-dev \
        build-essential \
        zlib1g-dev \
        zip \
        libjpeg8-dev \
        protobuf-compiler \
        libprotoc-dev \
        cmake && \
    rm -rf /var/lib/apt/lists/*

RUN pip3 install setuptools Cython wheel
RUN pip3 install numpy protobuf==3.16.0
RUN pip3 install --no-deps "onnx>=1.6.0,<=1.11.0"
RUN pip3 install \
        Pillow>=5.2.0 \
        wget>=3.2 \
        pycuda>=2017.1.1 \
        paho-mqtt

RUN mkdir /${REPOSITORY_NAME}
COPY ./ /${REPOSITORY_NAME}

WORKDIR /${REPOSITORY_NAME}

RUN wget ${LABEL_URL}
RUN wget ${MODEL_URL}