Dataset Overview:

The dataset consists of plant images stored in the train_images folder and json files containing the image labels.

The images have been labeled into 5 different classes - Cassava Bacterial Wilt (CBB), Cassava Brown Streak Disease (CBSD), Cassava Green Mottle Disease (CGM), Cassava Mosaic Disease (CMD), and Healthy”. The dataset also includes a .csv file that maps the image names to the corresponding labels.

Raw data

Dataset format:

The dataset is stored in the following format:

• train_images : A folder containing all plant images
• label_num_to_disease_map.json: json file with labels as keys and label descriptions as values.
• train.csv : A .csv file mapping image names to corresponding labels

Data preprocessing:

The images in the dataset are already preprocessed and ready to use. However, depending on your use case, additional preprocessing may be required.

usage:

This dataset can be used for a variety of purposes, such as image classification, object detection, and segmentation. It can be used to train machine learning models to detect plant diseases, or to develop automated plant diagnosis algorithms.