EfficientDet Tensorflow

Dockerfile

ARG BASE_IMAGE=nvcr.io/nvidia/l4t-base:r32.4.2
FROM ${BASE_IMAGE}

#
# install prerequisites - https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html#prereqs
#
RUN apt-get update && \
    apt-get install -y --no-install-recommends \
          python3-pip \
		  python3-dev \
		  gfortran \
		  build-essential \
		  libopenblas-dev \
		  libhdf5-serial-dev \
		  hdf5-tools \
		  libhdf5-dev \
		  zlib1g-dev \
		  zip \
		  libjpeg8-dev \
          libfreetype6-dev \
          libxml2-dev \
          libxslt1-dev \
    && rm -rf /var/lib/apt/lists/*

RUN pip3 install setuptools Cython wheel
RUN pip3 install numpy --verbose
RUN HDF5_DIR=/usr/lib/aarch64-linux-gnu/hdf5/serial/ pip3 install h5py==2.9.0 --verbose
RUN pip3 install numpy==1.16.1 future==0.17.1 mock==3.0.5 h5py==2.9.0 keras_preprocessing==1.0.5 keras_applications==1.0.8 gast==0.2.2 wrapt futures protobuf pybind11 --verbose

#
# TensorFlow (for JetPack 4.4 DP)
#
ARG JP_VERSION=44
ARG TF_VERSION=2.1.0
ARG NV_VERSION=20.4

ENV TENSORFLOW_URL=https://developer.download.nvidia.com/compute/redist/jp/v${JP_VERSION}/tensorflow/tensorflow-${TF_VERSION}+nv${NV_VERSION}-cp36-cp36m-linux_aarch64.whl
ENV TENSORFLOW_WHL=tensorflow-${TF_VERSION}+nv${NV_VERSION}-cp36-cp36m-linux_aarch64.whl

RUN wget --quiet --show-progress --progress=bar:force:noscroll --no-check-certificate ${TENSORFLOW_URL} -O ${TENSORFLOW_WHL} && \
    pip3 install ${TENSORFLOW_WHL} --verbose && \
    rm ${TENSORFLOW_WHL}

# 
# PyCUDA
#
ENV PATH="/usr/local/cuda/bin:${PATH}"
ENV LD_LIBRARY_PATH="/usr/local/cuda/lib64:${LD_LIBRARY_PATH}"
RUN echo "$PATH" && echo "$LD_LIBRARY_PATH"

RUN pip3 install pycuda --verbose

COPY ./efficientdet/ .
RUN pip3 install -r requirements.txt