Primary competition visual

Makerere Fall Armyworm Crop Challenge

Helping Uganda
$1 000 USD
Challenge completed over 3 years ago
Classification
Computer Vision
701 joined
155 active
Starti
Apr 14, 22
Closei
Jul 23, 22
Reveali
Jul 23, 22
About

The dataset contains images of maize crop leaves collected by research scientists from the Makerere Artificial Intelligence Lab, the Marconi Machine Learning Lab, and the National Crops Research Institute in Uganda. It contains 2699 images equally distributed across the healthy and fall armyworm classes.

The dataset does not contain any other attributes associated with the images. Images have not been subjected to any form of preprocessing.

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.

Files
Description
Files
This shows the submission format for this competition, with the ‘Image_id’ column mirroring that of Test.csv and the ‘Label’ column containing your predictions. The order of the rows does not matter, but the names of the ‘Image_id’ must be correct.
These are the IDs of the images you will use to test your model.
These are the IDs of the images you will use to train your model.
Images to use for training and testing.