![]() ![]() Recommend pulling from the NVIDIA images for models requiring a GPU Many images are available online and can be used as a base image. Docker can build images by reading the instructions from aĭockerfile. Secondly, you will need to create your own image. The NVIDIA Container Toolkit is also required to use CUDA within docker containers. In this section we list four steps you will have to follow in order create your docker image so that it is ready for submission.įirstly, you will need to install Docker. ĭocker is commonly used to encapsulate algorithms and their dependencies. The participant script must write each prediction using the format crossmoda_XXX_ in the /output folder.įor example, the prediction for the file /input/crossmoda_290_ must be located at /output/crossmoda_290_. The folder /input will contain all the test hrT2 scans with the format crossmoda_XXX_. The test set will be mounted into /input and the predictions must be written in /output. More specifically, a command will be executed when your Docker container is run (example: ` python3 run_inference.py`)Ĭommand must run the inference on the test set, i.e. The inference will be automatically performed using Docker. Pipeline requirements and execute your inference script. In particular, this container will locally replicate your Your code won't be sharedĪnd will be only used internally by the crossMoDA organisers.Īllows for running an algorithm in an isolated environment called aĬontainer. Submit their docker container for evaluation. Reason, participants must containerise their methods with Docker and The test set won't be released to the challenge participants. Docker Container Instructions Introduction crossMoDA papers will be part of theīrainLes workshop proceedings distributed by LNCS.Ģ. Submit longer papers to the MICCAI 2021 BrainLes Workshop post-proceedings. Later, participants will have the opportunity to MS Word format, directly from Springer ( link here).Īfter receiving the reviewers' feedbacks, participants will be allowed to submit their methods on open-access platforms (e.g., ArXiv). Submissions should use the LNCS template, available both in LaTeX and in Two structures (VS and Cochlea) with mean and standard deviation for the two metrics (Dice score and ASSD).
0 Comments
Leave a Reply. |