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.
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.
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.