The "Eyes on the Ground'' project is a collaboration between ACRE Africa, the Kenya Agricultural & Livestock Research Organization (KALRO), the International Food Policy Research Institute (IFPRI), and the Lacuna Fund, to create a large machine learning (ML) dataset that provides a close-up view of smallholder farmer's fields, with the aim of developing a Picture Based Insurance framework.
In order to help farmers across Africa manage agricultural risk, ACRE Africa uses image data to settle insurance claims and carry out loss assessment. ACRE has partnered with KALRO to review smartphone pictures of insured crops sent in by farmers to verify whether a farmer’s crops are damaged and to provide agricultural advisories. These advisories depend on whether a crop is damaged, and what the cause is of that damage, for instance whether the damage was related to weather, pests and diseases, or man-made factors such as fire, to evaluate an insurance claim and determine appropriate compensation.
Evaluating images for thousands of insured smallholder farmers to verify insurance claims and provide personalized agricultural advisories is time-consuming, slowing down claims settlement and increasing costs of the advisory service. ACRE Africa and KALRO are therefore looking at artificial intelligence to automate image processing, building on data that ACRE Africa, KALRO and IFPRI produced with support from the Lacuna Fund.
The objective of this challenge is to create a machine-learning algorithm to classify crops into categories: Good growth (G), Drought (DR), Nutrient Deficient (ND), Weed (WD), and Other (including pest, disease or wind damage). The data for this challenge is a collection of smartphone images of crops.
We invite you to build a model to classify damage type across multiple seasons. By knowing what type of damage a crop experiences, images can be fed into a model to indicate whether a crop was damaged, and needs to be evaluated for insurance payouts. KALRO and ACRE Africa’s personalized advisories for farmers will also depend on the classification of a farmer’s crop into these five categories.
We thank CGIAR Research Initiative on Digital Innovation for technical and financial supports that made this challenge possible.
The evaluation metric for this challenge is Log Loss.
Your submission should look like:
ID DR G ND WD other ID_YMXCDK 0.73 0.19 0.01 0.67 0.92 ID_B3HJ3N 0.03 0.45 0.99 0.46 0.20
The values can be between 0 and 1. 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.
These models often need to be applied at scale, so large ensembles aren’t encouraged. To incentivise more lightweight solutions, we are adding an additional submission criteria: your submission should take a reasonable time(~9 hours) to train and run inference.
We should be able to re-create your submission on a single-GPU machine (eg Nvidia P100) with less than 8 hours training and one hour inference. Additionally, the winning solutions will be implemented on a 4-core Virtual Machine with up to 16GB of RAM.
1st place: $5 000 USD
2nd place: $3 000 USD
3rd place: $2 000 USD
The winning solutions will
Payment will only be made after code review and sealing the leaderboard. Once confirmed, winners will be required to confirm their availability and collaborate with the hosts to implement their solutions.
There are 10 000 Zindi points available. You can read more about Zindi points here.
Competition starts on 27 October 2023.
Competition closes on 28 January 2024.
Final submissions must be received by 11:59 PM GMT.
We reserve the right to update the contest timeline if necessary.
About the International Food Policy Research Institute (IFPRI)
IFPRI provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition in developing countries. Established in 1975, IFPRI currently has more than 500 employees working in over 70 countries, and works with a wide range of partners. It is a research center of CGIAR, the world’s largest agricultural innovation network. IFPRI’s vision is a world free of hunger and malnutrition. Its mission is to provide research-based policy solutions that sustainably reduce poverty and end hunger and malnutrition.
About Agriculture and Climate Risk Enterprise (ACRE Africa)
ACRE Africa is a risk management solutions designer linking stakeholders to localized solutions such as insurance and climate change adaptation strategies to reduce agricultural and climate risks. At ACRE, we are determined to champion a paradigm shift towards equity, fairness and innovation to help unlock the full potential of agriculture by eliminating the stress and potential damage of climate variables for farmers in developing countries. Presently we work in Kenya, Rwanda, Tanzania and Zambia and projects in Uganda, Ghana, Malawi, Senegal, Nigeria, Zimbabwe, Ethiopia and Somali.
About Kenya Agricultural and Livestock Research Organization (KALRO)
KALRO is Kenya’s premier agricultural and livestock research organization, charged with the main mandate of promoting, streamlining, coordinating and regulating research in crops, livestock, genetic resources and biotechnology in Kenya. It is a corporate body created under the Kenya Agricultural and Livestock Research Act of 2013 to establish a suitable legal and institutional framework for the coordination of agricultural research in Kenya. KALRO’s objectives include expediting equitable access to research information, resources, and technology and promoting the application of research findings and technology in the field of agriculture. KALRO also, among others, formulates policy, makes policy recommendations to Kenya’s Cabinet Secretary on agricultural research, and KALRO prioritizes areas for, and coordinates, agricultural research in Kenya in line with the national policy on agriculture.
About CGIAR Research Initiative on Digital Innovation
CGIAR Research Initiative on Digital Innovation is a three-year program launched in 2022. The Initiative aims to contribute to the acceleration of sustainable and inclusive agrifood systems transformation by generating research-based evidence and innovative digital solutions. Its three priority research areas include improving access to digital innovation, the quality of information delivered, and the capacity of end users to make use of it. The Initiative brings together agri-food systems scientists and digital technology practitioners to research and implement innovative digital solutions across food, land, and water systems in the Global South.
About CGIAR Research Initiative on Diversification in East and Southern Africa
Launched as a crucial response to the challenges posed by climate change, the CGIAR Research Initiative on Diversification in East and Southern Africa is a transformative program, strategically designed to foster climate-resilient agriculture and sustainable livelihoods across 12 countries in East and Southern Africa. Its primary aim is to assist millions of smallholder farmers in intensifying and diversifying their maize-based farming practices, thereby mitigating risks and enhancing productivity through adaptation.
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This challenge is open to all.
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.
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 40% 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 60% 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 10 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 Reproducibility of submitted code guidelines detailed below. Failure to respond will result in disqualification.
To be eligible for cash prizes, 1st, 2nd, or 3rd on the final leaderboard will release their top solutions under an open source license for ongoing use and learning.
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. 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.
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.
Payment will be made after code review and sealing the leaderboard.
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.
A README markdown file is required
It should cover:
Your code needs to run properly, code reviewers do not have time to debug code. If code does not run easily you will be bumped down the leaderboard.
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions
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