Dear Contestants, Apologies for the delay in data description. This year, we packaged the data as tar shards so you can load it directly with the Webdataset library. https://pypi.org/project/webdataset/ For the labeled training set, we ensured that each label appeared in every tar shard file and did our best to distribute patches evenly across the shards. They are randomly distributed with a fixed seed. In the current version of the data description, we provided an example for you to load the packaged data using webdataset. See https://www.synapse.org/Synapse:syn74274097/wiki/639588 I will update the data description in the following days, but I think considering there are contestants who have previous experience. It would be clearer to be addressed here as well. For the evaluation, we follow the tradition from past years' challenges and ask you to submit ONE CSV file with one column for the patch names and another for the predicted labels for the validation set. We will release the validation set (in tar shards) and unlabeled training images (in tif files), along with scripts to patch and package the large tif images, in the coming days. Feel free to ask any questions. ### Update for data entry ### Thanks, @rohanthakar, for pointing out the visualisation issue with the data entry. To download data, please register according to the "Data Page" at https://www.synapse.org/Synapse:syn74274097/wiki/639588, as described in the "Data Access" section. After registration, the data can be accessed at https://www.synapse.org/Synapse:syn74488419 for Task 5. ### Update on 14-06-2026 for Containerization ### We updated a containerization template and an inference example at https://github.com/IUCompPath/BraTS-Path-2026-Docker-Submission-Kit A small debug/demo set will also be provided at the data entry page. Feel free to reach out with any problems regarding containerization and other issues. ### Update on 13-07-2026 ### We added some print out sections in the github repo. We also recommend contestants to have printout during running the inference, which helps debugging and easier to pin-point problematic lines. It is only 10 days to the deadline, we would suggest to start dockerization if not yet. If you have no experience with docker before, it will be problematic and time consuming. Cheers, Jayden

Created by Suhang You jaydenyou
Hi @kechen0207, We will accept the file upload in the team project space. In [https://challenges.synapse.org/Challenges/DetailsPage/Task5?id=syn74274097#Submission](url) , using the upload file button as you uploaded the csv files for validation. Cheers, Jayden
Hi @jaydenyou, What should we submit for the final testing phase? A docker image upload via 'docker push', or in the format of a tar file via 'file upload' in the team project space? Regards, Ke CHEN
Hi Jayden @jaydenyou, Thank you for your reply! It is very helpful.
Hi @lzhao, The template is just an example to help you roughly understand how to add the scripts and place the functions. If you have your own inference steps and dependencies, please feel free to modify as you wish, as long as the input and output match. However, I do recommend including an argparse argument (with a default int value) for batch size in case it consumes a large amount of GPU VRAM. Using mixed precision will also help. Cheers, Jayden
Hi Jayden @jaydenyou, Thanks again for the container template. I have two clarification questions about the src/directory structure: 1. Are we allowed to add new subfolders and files under src/ other than the template's defaults ? For example, a folder holding model-definition/helper code and a .json configuration file. The container interface (run.py, input/output, predictions.csv) would remain unchanged; these additions are only imported by our inference code. 2. Are we allowed to create subfolders inside ckpts/ and foundation_model_weights/ to organize files? 3. Are we allowed to add customized functions in inference.py, as well as inference_dependencies.py (and ignore the ones not needed) and import them in inference.py? Thank you for your clarification!
Hi Jayden @jaydenyou, Got it, thanks for the resposne!
Hi @lzhao, For this challenge submission in the test phase, we only require inference code. Cheers, Jayden
Hi Jayden @jaydenyou, Thanks for these updates! The containerization template is very helpful. Just wanted to confirm that, the container submission requires only the inference code, and no training code, correct? Thanks!
@rohanthakar Let me know if any access issue. @fouzul.h In case you are facing the same issue please check the post above.
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@jaydenyou where can we find the .tar shards for training ? we are facing a difficulty to find those as we are participating for the first time please guide us where can we find those
@shubham.innani Added description in the submission page. Cheers, Jayden
Hi @jaydenyou, Thank you for the update. https://www.synapse.org/Synapse:syn74274097/wiki/639582#:~:text=Task%205%3A%20Pathology%20Task%20(CSV) According to instructions here, this are the expected column names and predictions. Can you please confirm?

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