# Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch FROM nvcr.io/nvidia/pytorch:19.12-py3 # Install dependencies (pip or conda) RUN pip install -U gsutil # RUN pip install -U -r requirements.txt # RUN conda update -n base -c defaults conda # RUN conda install -y -c anaconda future numpy opencv matplotlib tqdm pillow # RUN conda install -y -c conda-forge scikit-image tensorboard pycocotools ## Install OpenCV with Gstreamer support #WORKDIR /usr/src #RUN pip uninstall -y opencv-python #RUN apt-get update #RUN apt-get install -y gstreamer1.0-tools gstreamer1.0-python3-dbg-plugin-loader libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev #RUN git clone https://github.com/opencv/opencv.git && cd opencv && git checkout 4.1.1 && mkdir build #RUN git clone https://github.com/opencv/opencv_contrib.git && cd opencv_contrib && git checkout 4.1.1 #RUN cd opencv/build && cmake ../ \ # -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \ # -D BUILD_OPENCV_PYTHON3=ON \ # -D PYTHON3_EXECUTABLE=/opt/conda/bin/python \ # -D PYTHON3_INCLUDE_PATH=/opt/conda/include/python3.6m \ # -D PYTHON3_LIBRARIES=/opt/conda/lib/python3.6/site-packages \ # -D WITH_GSTREAMER=ON \ # -D WITH_FFMPEG=OFF \ # && make && make install && ldconfig #RUN cd /usr/local/lib/python3.6/site-packages/cv2/python-3.6/ && mv cv2.cpython-36m-x86_64-linux-gnu.so cv2.so #RUN cd /opt/conda/lib/python3.6/site-packages/ && ln -s /usr/local/lib/python3.6/site-packages/cv2/python-3.6/cv2.so cv2.so #RUN python3 -c "import cv2; print(cv2.getBuildInformation())" # Create working directory RUN mkdir -p /usr/src/app WORKDIR /usr/src/app # Copy contents COPY . /usr/src/app # Copy weights #RUN python3 -c "from models import *; \ #attempt_download('weights/yolov3.pt'); \ #attempt_download('weights/yolov3-spp.pt')" # --------------------------------------------------- Extras Below --------------------------------------------------- # Build and Push # t=ultralytics/yolov3:v0 && sudo docker build -t $t . && sudo docker push $t # Run # sudo nvidia-docker run --ipc=host ultralytics/yolov3:v0 python3 detect.py # Pull and Run with local directory access # t=ultralytics/yolov3:v0 && sudo docker pull $t && sudo nvidia-docker run -it --ipc=host -v "$(pwd)"/coco:/usr/src/coco $t # Kill all # sudo docker kill "$(sudo docker ps -q)" # Kill all image-based # sudo docker kill $(sudo docker ps -a -q --filter ancestor=ultralytics/yolov3:v0) # Run bash for loop # sudo nvidia-docker run --ipc=host ultralytics/yolov3:v0 while true; do python3 train.py --evolve; done