AI Crowd showing wrong submission id

Hi, looks like you are on the wrong link?

In case you want to lock 161132, it is a submission for Taxi Problem (not Youtube assignment).

The correct link would be:
https://www.aicrowd.com/challenges/iit-m-2021-assignment-2/problems/rl-assignment-2-taxi/submissions/lock

i.e. each problem has one submission that need to be locked.

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Submission Upload Error

Hi @sumedh_gupte,

It is now fixed, please make your new submissions.

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AI Crowd error

Yes.

We have resolved the issue, and you should be able to lock the submission. Please let us know in case you continue to face any issue.

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AI Crowd error

Hi @ee19b095, can you share on which page are you facing it so we can troubleshoot on our side?

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No attribute 'SIGALRM' issue in Windows 10

Hi @woosung_choi,

You can comment out lines 27 & 28 while running on windows as a quick fix. (as well as in your submissions).
We overwrite music_demixing.py which will have code for Linux – during evaluation so it wouldn’t change anything.

Meanwhile, I can check if we can port the solution we used in another project i.e. Flatland.

Coindently by MLerik & spmohanty only from the GitHub issue link you shared.

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Dataset LifeCLEF 2020

It can be because of unstable internet.

You can try the mirror links provided in the challenge:
https://www.aicrowd.com/clef_tasks/24/task_dataset_files?challenge_id=213

It has 2 splits, which should make downloading easier.
Let us know how it goes!

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Dataset LifeCLEF 2020

Hi @radha_raja,

The download link on the above link looks to be working.

What issue are you facing?

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Questions about the size limit of the training model

Hi @yue,

It is possible that your file isn’t pushed properly via git lfs, hence torch.load can’t read it.

Related thread which might be useful to you

In case you are stuck, please let me know your submission ID and I can help in debugging.

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Questions about the size limit of the training model

No, I guess you looked for pricing @ GitHub.

We use our own-hosted version at gitlab.aicrowd.com, which you need to use for making submissions as well. It doesn’t have such limits or pricing and is free for the participants to use for the purpose of the AIcrowd challenges.

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Questions about the size limit of the training model

The normal maximum file size is 50MB.

For uploading the larger files, you can submit files of size up to GBs via git lfs.
In case you are not familiar with it can check the quick help doc here: How to upload large files (size) to your submission

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(Solved) Running test_submission.py runs into _pickle.UnpicklingError: invalid load key, 'v'

Hi @paul_puntschart,

Happy that you managed to resolve it!

Meanwhile, in case anyone is reading this in the future.

This might be happening because the file isn’t properly uploaded via git-lfs (or not uploaded at all). Please browse your repository in the browser to verify the file. You can do the following to fix the problem:

• reupload by git lfs push origin master
• verify .gitattributes if your lfs entry is mentioned (at repository root)
• clone repository freshly in new folder, and try uploading from that (in case your current repository’s settings are messed up locally)

[More about git-lfs]

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Scores for private runs are now available! 🎉

Hi everyone,

The scores from the private runs are now available!

Tracking Leaderboard
https://www.aicrowd.com/challenges/airborne-object-tracking-challenge/leaderboards?challenge_leaderboard_extra_id=901

Detection Leaderboard
https://www.aicrowd.com/challenges/airborne-object-tracking-challenge/leaderboards?challenge_leaderboard_extra_id=902

Unrated Leaderboard (all the submitted submissions)
https://www.aicrowd.com/challenges/airborne-object-tracking-challenge/dynamic_contents

NOTE:
We are in the process of doing the due diligence on the top submissions and have reached out to the respective participants and teams. We aim to finish up the due diligence in the coming weeks and will announce the winners as soon as it is done!

You can also view your selected submission’s score by “Submissions” tag -> “View”, and private scores would be visible next to public ones.

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The dataset after the challenge

Hi @ivo_georgiev,

Yes, the dataset (via s3 and dataset helper scripts) and content generated as part of this challenge will remain accessible after the challenge.

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Instruction for Task 3 submissions

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Fail to submit

Hi @TaoLiu,

Only 5 successful submissions are counted. The failed one doesn’t.

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Fail to submit

Hi @here,

The submission limit is 5 successful submissions/per task for the whole challenge.

For task 3, given the submissions are evaluated with delay, your first 5 successful submissions will be counted.

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Instruction for Task 3 submissions

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Instruction for Task 3 submissions

About evaluations in this task

In this task, the developed methods will be evaluated on the testing set by the organizers locally by running them within a docker provided by the challengers.

Docker instructions

You must provide a built image containing your method. Please refer to the Docker documentation to build your image.

During the evaluation, your docker will be executed by the organizers on the test dataset, and the output scores will be processed similarly as in task 2 to compute the C-index, using the following command line:

docker run -v /datalocation:/data -v /outputlocation:/output mydockerimage /bin/bash -c 
    "sh predict.sh /data/[PatientID]PET.nii.gz /data/[PatientID]CT.nii.gz /data/[PatientID]SegMask.nii.gz /output/output_score.csv”

Update: An example with Dockerfile and few sample scripts are provided here.

How to submit the submissions

1. Save your docker image:

docker save --output submission-v1.tar your_image_name

2. Upload the docker image as submission:

aicrowd submission create -c miccai-2021-hecktor -f submission-v1.tar

In case aicrowd-cli is not installed you can do so via pip install aicrowd-cli

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How to submit for different tasks?

Hi @jeff_vanoss,

The submissions will be starting later today along with instructions.

Sorry for causing confusion.

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Not able to access the dataset

Hi @harman_singh, unfortunately in this challenge, the dataset isn’t available after the challenge.

I would encourage you to check out any other challenge in which you might be interested.
https://www.aicrowd.com/challenges/

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