Palm oil is an edible vegetable oil derived from the mesocarp (reddish pulp) of the fruit of the oil palms. The oil is used in food manufacturing, beauty products, and as biofuel.
The objective of this challenge is to create a semi-supervised machine learning algorithm to count the number of palm oil trees in an image.
This will aid farmers to determine the number of trees on their plot and estimated crop yield. The semi supervised nature of this solution will allow this solution to be applied to other plantations such as banana palms.
L'huile de palme est une huile végétale comestible dérivée du mésocarpe (pulpe rougeâtre) du fruit du palmier à huile. Cette huile est utilisée dans l'industrie alimentaire, les produits de beauté et comme biocarburant.
L'objectif de ce défi est de créer un algorithme d'apprentissage automatique semi-supervisé pour compter le nombre de palmiers à huile dans une image.
Cela aidera les agriculteurs à déterminer le nombre d'arbres sur leur parcelle et à estimer le rendement des cultures. La nature semi-supervisée de cette solution permettra de l'appliquer à d'autres plantations telles que les palmiers bananiers.
About Digital Africa
Launched in 2018, the Digital Africa initiative's mission is to strengthen the capacity of African digital entrepreneurs to design and deploy disruptive innovations at scale to serve the real economy. The initiative brings together a range of partners of all nationalities committed to African digital entrepreneurs, at the forefront of which is the French Development Agency (AFD).
Digital Africa a pour mission de renforcer la capacité des entrepreneurs africains à concevoir et déployer à grande échelle des innovations numériques au service de l’économie réelle. Agissant comme un catalyseur, Digital Africa rassemble un ensemble de partenaires de toutes nationalités - startups, chercheurs, incubateurs, financiers institutionnels, venture capitalists, cluster techs - engagés auprès des entrepreneurs numériques africains, au premier rang desquels se trouve Proparco, en qualité d’associé unique.
Created in 1978 under the name of Direction et Contrôle des Grands Travaux (DCGTx), the Bureau National d'Etudes Techniques et de Développement (BNETD) is a design office created to contribute to the development of Ivory Coast and the African countries in which it is present. In Ivory Coast, it is responsible for designing, monitoring studies and project management of public works, assisting and advising the government in the implementation of its road, water and energy infrastructure development policy.
Créé en 1978 sous la dénomination de la Direction et Contrôle des Grands Travaux (DCGTx), le Bureau National d'Etudes Techniques et de Développement (BNETD) est un bureau d'études créé dans le but de contribuer au développement de la Côte d'Ivoire et des pays africains dans lesquels il est présent. En Côte d'Ivoire, il a un rôle de conception d'études et de maîtrise d'œuvre pour de nombreux travaux publics et conseille l'État dans la programmation et la mise en œuvre de sa politique de développement d'infrastructures routières, hydrauliques et d'énergie.
Established in 2019, data354 is the first advisory firm pure-player data in West Africa. Our mission is to foster the emergence of data expertise in Africa by supporting our clients throughout their data journeys and help them to become more data-driven and to get most out of their data using the unique combination of our expertise in Strategy and Management Advisory and our mastery of data technologies.
Créée en 2019, data354 est le premier cabinet de conseil en data pure player en Afrique de l'Ouest. Notre mission est de favoriser l'émergence d'une expertise Data en Afrique en accompagnant nos clients tout au long de leur parcours data, les aider à devenir plus data-driven et à tirer le meilleur parti de leurs données grâce à notre combinaison unique d'expertise en conseil en Stratégie et Management et notre expertise Technologique.
About INVESTIV (investivgroup.com)
INVESTIV is a company specialising in precision agriculture and the use of drones. Created in 2017, it is positioned as a pioneer in the use of drones in agriculture in West Africa. It offers its partners and clients technical and innovative solutions that allow them to reduce losses related to phytosanitary problems, to know with precision the state and dimensions of their land, to monitor the evolution of their agricultural activities and to carry out technical studies prior to the implementation of their agricultural project.
INVESTIV est une entreprise spécialisée dans l'agriculture de précision et l'utilisation de drones. Créée en 2017, elle se positionne comme un pionnier de l'utilisation des drones dans l'agriculture en Afrique de l'Ouest. Elle propose à ses partenaires et clients, des solutions techniques et innovantes qui leur permettent de réduire les pertes liées aux problèmes phytosanitaires, de connaître avec précision l'état et les dimensions de leurs terres, de suivre l'évolution de leurs activités agricoles et de réaliser des études techniques préalables à la mise en œuvre de leur projet agricole.
About Data4DigitalAfrica Project
Developed by Digital Africa, Data4DigitalAfrica is an open data infrastructure that aims to make data accessible to African startups and entrepreneurs through:
Développée par Digital Africa, Data4DigitalAfrica est une infrastructure de données ouvertes qui vise à rendre les données accessibles aux startups et entrepreneurs africains à travers:
The error metric for this competition is the Root Mean Squared Error.
For every row in the dataset, submission files should contain 2 columns: Image_ID and Count.
Your submission file should look like this:
Image_ID Count GL5_15360_8192 5 GL5_15360_9216 12
1st man - $4 000 USD either as an individual first man or majority male team.
1st woman - $4 000 USD either as an individual first woman or majority female team.
1st person from Ivory Coast - $2 000 USD, different from top man or woman prize.
Competition starts on 22 February 2023.
Competition closes on 9 April 2023.
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 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. The winners’ solutions will be shared in a well-organized code repository with proper documentation, and added to the Radiant MLHub model repository.
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.
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.
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