The task is to classify each cassava image into five categories indicating - plant with a certain kind of disease or healthy leaf.
Organizers introduced a dataset of 21,367 labeled images collected during a regular survey in Uganda. Most images were crowd-sourced from farmers taking photos of their gardens, and annotated by experts at the National Crops Resources Research Institute (NaCRRI) in collaboration with the AI lab at Makerere University, Kampala.
It seems that there are already a few submissions/notebooks with PL.
install this tooling
A simple way how to use this basic functions:
! pip install https://github.com/Borda/kaggle_cassava-leaf-disease/archive/main.zip
run notebooks in Colab
I would recommend uploading the dataset to you personal gDrive and then in notebooks connect the gDrive which saves you lost of time with re-uploading dataset when ever your Colab is reset... :]
Training progress with ResNet50 with training for 10 epochs: