The PlantVillage Dataset is meticulously structured into training, testing, and validation folders, each containing 15 subfolders for different plant disease classes.

This dataset is created for the project under Omdena’s Local Chapter to develop a Rice Disease Classifier using open-source data and computer vision techniques.

Explore the Germination Seedling Detection dataset from Gts, designed to enhance vertical farming efficiency.

This dataset images are collected from tropical Malaysian forests and encompasses a diverse range of arthropod species captured under various lighting and environmental conditions.

Plant disease is a deviation from the normal state of a plant that disrupts or alters its vital functions. Plant diseases can lead to significant yield losses.

This dataset is invaluable for research and development in plant biology, agricultural automation, and computer vision. Researchers and practitioners can leverage these annotated images and masks for tasks such as plant phenotyping, disease detection, and growth monitoring.

Manually collected image dataset of sugarcane leaf disease. It has mainly five main categories in it. Healthy, Mosaic, Redrot, Rust, and Yellow disease.

There are over 20 types of mushrooms.

This dataset contains images and meta data for crop disease classification. For training purposes, it should be split into three sets necessary.

The application of Artificial Intelligence (AI) has been evident in the agricultural sector recently.