Face masks have become a common public sight in the last few months. The Centers for Disease Control (CDC) recently advised the use of simple cloth face coverings to slow the spread of the virus and help people who may have the virus and do not know it from transmitting it to others. Wearing masks is broadly recognised as critical to reducing community transmission and limiting touching of the face.

In a time of concerns about slowing the transmission of COVID-19, increased surveillance combined with AI solutions can improve monitoring and reduce the human effort needed to limit the spread of this disease. The objective of this challenge is to create an image classification machine learning model to accurately predict the likelihood that an image contains a person wearing a face mask, or not. The total dataset contains 1,800+ images of people either wearing masks or not.

Your machine learning solution will help policymakers, law enforcement, hospitals, and even commercial businesses ensure that masks are being worn appropriately in public. These solutions can help in the battle to reduce community transmission of COVID-19.

About #ZindiWeekendz

The Zindi community is joining the fight against COVID-19! #ZindiWeekendz are virtual weekend hackathons hosted by Zindi. This series of #ZindiWeekendz throughout April and May 2020 focuses specifically on COVID-19.

In a time of lockdowns, remote work, and general uncertainty, #ZindiWeekendz offer data scientists the opportunity to continue to develop their skills while contributing to practical, open-source AI solutions to help in the battle against COVID-19.

All winning solutions will be shared as a public good on GitHub. We are committed to supporting partners implement these solutions and encourage anyone who is interested to reach out to us at zindi@zindi.africa.

About Microsoft (microsoft.com)

This hackathon is sponsored by Microsoft (Nasdaq “MSFT” @microsoft). Microsoft enables digital transformation for the era of an intelligent cloud and an intelligent edge. Microsoft has operated in Africa for more than 25 years. In that time they have built strong partnerships across the continent, helped bridge gaps in infrastructure, connectivity and capability, and are working to empower countries in Africa to digitally transform while creating sustained societal impact. Earlier this year, Microsoft opened Africa’s first hyper-scale data centers in Johannesburg and Cape Town, South Africa. Most recently, the company also announced the opening of two Africa Development Centers in Nairobi and Lagos, where world-class African talent can create innovative solutions for local and global impact.

Teams and collaboration

You may participate in this competition as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the highest number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

If external data is allowed you may only use data that is freely available to everyone. You must send it to Zindi to confirm that it is allowed to be used and then it will appear on the data page under additional data.

You may use pretrained models as long as they are openly available to everyone.

You are allowed to access, use and share competition data for any commercial,. non-commercial, research or education purposes, under a CC-BY SA 4.0 license.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.

Submissions and winning

You may make a maximum of 10 submissions per day. Your highest-scoring solution on the private leaderboard at the end of the competition will be the one by which you are judged.

If your solution places 1st, 2nd, or 3rd in the final ranking, you will be required to submit your winning solution code to us for verification and you thereby agree to share your code on GitHub as a public good to the sector. We also encourage all participants to share their solutions on GitHub.

You will have until 17:00 GMT on Wednesday 22 April 2020 to submit your code for review. Submit your code to zindi@zindi.africa with subject line "Challenge name position # - team name or username" Regardless of any public announcement of winners, Zindi reserves the right to disqualify any user, team if the code does not reproduce the winning submission.

Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 50% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers the other 50% of the test dataset, will be made public and will constitute the final ranking for the competition.

If you are in the top three at the time the leaderboard closes, we will email you to request your code. On receipt of email, you will have 48 hours to respond and submit your code following the submission guidelines detailed below. Failure to respond will result in disqualification.

If two solutions earn identical scores on the leaderboard, the tiebreaker will be the date and time in which the submission was made (the earlier solution will win).

The winners will be paid via bank transfer, PayPal, or other international money transfer platform. International transfer fees will be deducted from the total prize amount, unless the prize money is under $500, in which case the international transfer fees will be covered by Zindi. In all cases, the winners are responsible for any other fees applied by their own bank or other institution for receiving the prize money. All taxes imposed on prizes are the sole responsibility of the winners.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

The evaluation metric for this challenge is Log Loss.

Your submission file should look like:

id                                    label
ttuqxjhrmdqhppfxrbzgyciipwdxcf.jpg     0.99
qmltykiislwklsklnzhcsrfsqwmaun.jpg     0.23
lkzeblenqbovljxpucpsufmprjxxqn.jpg     0.67

1st: $125

2nd: $100

3rd: $75

Top 10 will also receive access to valuable online data science learning content for approximately six months.

Competition closes on 19 April 2020.

Final submissions must be received by 11:59 PM GMT.

We reserve the right to update the contest timeline if necessary.