You can start with this baseline submission that’s based on MMDetection, which itself is based on PyTorch:
Clone the above repository, change your username in the aicrowd.json file, and then follow the instructions here (from # Add AICrowd git remote endpoint forward):
This way, you should be able to upload a valid submission and get on the leaderboard with the baseline result (AP=0.478 and AR=0.687).
After that, you can simply swap the included .pth model with your own - just change the run.sh script with the correct model filename. Keep in mind that the baseline submission also has scripts for training & evaluation, so you can use these tools to your advantage.
I ran into some problems while trying to use my own models with this baseline submission, but after cloning the repo again and changing only the model file, it works once more (the repo was updated recently).
I also don’t see my repo updated after the latest submissions (it did update for the first couple of submissions in February, and after that it stopped updating with every submission), but everything is successfully uploaded nonetheless. So just be mindful that you upload your model to LFS and push it, and you should be fine.
Best of luck!