Dockerfile

# Edit the base image here, e.g., to use 
# TENSORFLOW (https://hub.docker.com/r/tensorflow/tensorflow/) 
# or a PYTORCH (https://hub.docker.com/r/pytorch/pytorch/) base image


FROM python:3.7-slim

RUN apt-get update
RUN apt-get install ffmpeg libsm6 libxext6  -y
RUN apt-get install wget -y

RUN groupadd -r algorithm && useradd -m --no-log-init -r -g algorithm algorithm

RUN mkdir -p /opt/algorithm /input /output \
    && chown algorithm:algorithm /opt/algorithm /input /output

USER algorithm

WORKDIR /opt/algorithm

ENV PATH="/home/algorithm/.local/bin:${PATH}"

RUN python -m pip install --user -U pip

# Install required packages
# e.g. `python -m pip install sklearn==...`
RUN wget https://ultralytics.com/assets/Arial.ttf
#RUN mv Arial.ttf /opt/algorithm/.config/Ultralytics/
COPY --chown=algorithm:algorithm requirements.txt /opt/algorithm/
RUN python -m pip install --user --upgrade pip
RUN python -m pip install --user -rrequirements.txt
RUN python -m pip show imagecodecs

COPY --chown=algorithm:algorithm process.py /opt/algorithm/
COPY --chown=algorithm:algorithm weights.h5 /opt/algorithm/
COPY --chown=algorithm:algorithm model /opt/algorithm/
COPY --chown=algorithm:algorithm yolov5/ /opt/algorithm/
# Copy additional files, such as model weights
# e.g. `COPY --chown=algorithm:algorithm weights.pth /opt/algorithm/weights.pth`

ENTRYPOINT python -m process $0 $@

## ALGORITHM LABELS ##

# These labels are required
LABEL nl.diagnijmegen.rse.algorithm.name=airogs_algorithm

# These labels are required and describe what kind of hardware your algorithm requires to run.
LABEL nl.diagnijmegen.rse.algorithm.hardware.cpu.count=1
LABEL nl.diagnijmegen.rse.algorithm.hardware.cpu.capabilities=()
LABEL nl.diagnijmegen.rse.algorithm.hardware.memory=1G
LABEL nl.diagnijmegen.rse.algorithm.hardware.gpu.count=0
LABEL nl.diagnijmegen.rse.algorithm.hardware.gpu.cuda_compute_capability=
LABEL nl.diagnijmegen.rse.algorithm.hardware.gpu.memory=