This project is a tomato disease classifier using machine learning algorithms like random forest and XGBoost The steps to run this classifier are:
Step 1 : download the data from kaggle
Step 2 : Split data into training and testing sets. Keep in mind the computation power of your PCs and select number of training examples accordingly. Here, I have taken 400 training images per calss and 100 testing images per class.
Step 3 : Provide the path to training and testing images folders in the code and run all the blocks of code.