Docker Containers for Submission with mmdetection

When I first started working on this challenge I spent a lot more time trying to get the submissions working without errors than I did on training the models. Much of this time was spent trying to debug the building and execution of the Docker containers.

To avoid this problem I have created two Docker images for mmdetection :

  • skooch/mmdet-aicrowd - contains PyTorch 1.2, CUDA 10.0, and mmdet v1.0rc1
  • skooch/mmdet-aicrowd-latest - contains PyTorch 1.6, CUDA 10.1, and the latest version of mmdet

If you are using mmdetection, you can build your containers from these images and your submissions will run faster (since the images are already built) and hopefully your submissions will fail less.

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I also have an image for Detectron2 - the latest version - with PyTorch 1.7, CUDA 10.1, torchvision 0.8.1. Note that the starter notebook uses an older version of Detectron and PyTorch which I have not checked for compatibility.

  • skooch/detectron2

This image is based on the official Detectron2 Docker image, you would need to copy your code into it and install aicrowd tools like coco, pycocotools, aicrowd_api, and aicrowd-repo2docker.