Fall armyworm is a devastating pest in Africa, where it has no natural predators - African farmers say the pest causes average maize losses of 31% annually. Maize is the most widely grown crop in Africa and a staple for around half the continent’s people - over 300 million Africans depend on the crop for food and nutritional security. For smallholder farmers in particular, maize is popular for its wide adaptability, valuable by-products and high yields.
Because of this reliance on staple crops for food security, Viral pests and diseases like fall armyworm are one of the leading causes of food insecurity and poverty in Africa. Thus there is an urgent need to design early intervention mechanisms to help prevent crop losses for smallholder farmers.
In this challenge, your objective is to classify if a plant has been affected by a fall armyworm. This is a binary image classification challenge. The solution will be deployed as part of a mobile-based edge application which can be used by smallholder farmers in Uganda and the rest of Africa to carry out field-based diagnosis and intervene before fall armyworm devastates their maize crop for the season.
Resource restriction
To make this challenge accessible to all, there are restrictions on run time. You are allowed a maximum of 7 hours’ train time and 2 hours’ inference time on the whole test set, with a maximum 1 minute inference per image.
We encourage you to use Google Colab which allows you access to a NVIDIA Tesla K80. If you choose to use a different GPU, it may not exceed the specs of an NVIDIA Tesla K80.
About Makerere AI Lab (air.ug)
The Artificial Intelligence and Data Science lab specialises in the application of artificial intelligence and data science -including, for example, methods from computer vision, natural language processing and predictive analytics-to problems in the developing world.
Applications: Natural language processing for under-resourced languages, automated diagnosis of both crop and human diseases, auction design for mobile commodity markets, analysis of traffic patterns in African cities, and of telecoms and remote sensing data for anticipating the spread of infectious diseases.
About Marconi Machine Learning Lab (marconilab.org)
The Marconi Society Machine Learning Laboratory, Makerere University is a research initiative of netLabs! UG, Makerere University that focuses on machine learning research in diverse areas including Agriculture, Health and Natural Language Processing.
About Makerere University Research Innovations Fund (RIF) (rif.mak.ac.ug)
This work is supported by the Makerere University Research Innovations Fund (RIF), a Lacuna and a Labelbox education license.
1st Place: $500 USD
2nd Place: $300 USD
3rd Place: $200 USD
The evaluation metric for this competition is Area Under the Curve (AUC).
For every row in the dataset, submission files should contain 2 columns: ID and Target.
Where 1 indicates that the image has been affected by a fall armyworm and 0 if it has not been affected.
Your submission file should look like this (numbers to show format only):
Image_ID Target
ID_D9ONL553 0.13
ID_263YTILY 0.87
Competition closes on 23 July 2022.
Final submissions must be received by 11:59 PM GMT.
We reserve the right to update the contest timeline if necessary.
Teams and collaboration
You may participate in competitions 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 total 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 immediately disqualified from the platform.
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).
The Zindi data scientist who sets up a team is the default Team Leader but they can transfer leadership to another data scientist on the team. The Team Leader can invite other data scientists to their team. Invited data scientists can accept or reject invitations. Until a second data scientist accepts an invitation to join a team, the data scientist who initiated a team remains an individual on the leaderboard. No additional members may be added to teams within the final 5 days of the competition or last hour of a hackathon.
The team leader can initiate a merge with another team. Only the team leader of the second team can accept the invite. The default team leader is the leader from the team who initiated the invite. Teams can only merge if the total number of members is less than or equal to the maximum team size of the competition.
A team can be disbanded if it has not yet made a submission. Once a submission is made individual members cannot leave the team.
All members in the team receive points associated with their ranking in the competition and there is no split or division of the points between team members.
Datasets and packages
The solution must use publicly-available, open-source packages only.
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.
You may use pretrained models as long as they are openly available to everyone.
The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.
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.
You may make a maximum of 300 submissions for this competition.
Before the end of the competition you need to choose 2 submissions to be judged on for the private leaderboard. If you do not make a selection your 2 best public leaderboard submissions will be used to score on the private leaderboard.
During the competition, your best public score will be displayed regardless of the submissions you have selected. When the competition closes your best private score out of the 2 selected submissions will be displayed.
Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 20% 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 80% of the test dataset, will be made public and will constitute the final ranking for the competition.
Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.
If you are in the top 20 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 your solution places 1st, 2nd, or 3rd on the final leaderboard, you will be required to submit your winning solution code to us for verification, and you thereby agree to assign all worldwide rights of copyright in and to such winning solution to Zindi.
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).
If the error metric requires probabilities to be submitted, do not set thresholds (or round your probabilities) to improve your place on the leaderboard. In order to ensure that the client receives the best solution Zindi will need the raw probabilities. This will allow the clients to set thresholds to their own needs.
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. The top 3 winners or team leaders will be required to present Zindi with proof of identification, proof of residence and a letter from your bank confirming your banking details.Winners will be paid in USD or the currency of the competition. If your account cannot receive US Dollars or the currency of the competition then your bank will need to provide proof of this and Zindi will try to accommodate this.
Payment will be made after code review and an introductory call with the host.
Please note that due to the ongoing Russia-Ukraine conflict, we are not currently able to make prize payments to winners located in Russia. We apologise for any inconvenience that may cause, and will handle any issues that arise on a case-by-case basis.
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.
Zindi is committed to providing solutions of value to our clients and partners. To this end, we reserve the right to disqualify your submission on the grounds of usability or value. This includes but is not limited to the use of data leaks or any other practices that we deem to compromise the inherent value of your solution.
Zindi also reserves the right to disqualify you and/or your submissions from any competition if we believe that you violated the rules or violated the spirit of the competition or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.
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.
Reproducibility of submitted code
Data standards:
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions