Classification of COVID-19 Through XRay images

File Description

• Training: Contains COVID and Normal directories. Each folder contains 256x256 .png XRay images of patients with and without COVID 19 respectively.
• Testing: Contains the XRay images to be classified.

See submission guidelines for more details

The ranking is displayed based on the F1 Score of the submission. "Training" directory contains the data required for training.

The output of the model should be "output.csv" containing two columns:

• Filename (name of the file. i.e. 1, 2, 3, etc)
• Label (COVID or NORMAL)

The submission should be a .csv file, in the following format:

How to make a submission?

1. Click on "My Submission"
2. On the next page, click on "+ New Submission"
3. Upload your CSV in the next page and click on "Submit for Review"

Please note:

1. You must submit your CSV file by uploading the CSV in the "My Submissions" section of this challenge.
2. Your submission will be auto graded and you will be able to see your results instantly.
3. If there is any error in the submission, your final score will be marked as 0.

• Each team can have 2-3 students
• Participants are provided with a training set (labelled data) and a testing set (unlabeled) which they need to predict and submit the predictions of. The submitted predictions will then be automatically graded by dockship.io and the F1 score will be used to rank you on a leaderboard.
• Each team gets up to 20 submissions per day.
• There are two leaderboards, Public and Private. The winners will be those with the highest score in both the public and private leaderboards at the end of the submission period and will be announced on Jan 25th, 2022 .
• Winners may be asked to submit their code for review if required by judges.

Note: The public leaderboard shown does not show your final ranking and is not the final leaderboard. There is also a private leaderboard that will contribute to your final ranking in the competition.

All teams that successfully make a submission get a certificate at the end of the challenge.

Prizes to be awarded to the winners:

• 1st place winner: 600 AED

• 2nd place winner: 400 AED