The Plants and Crops dataset is a comprehensive crop image dataset for the agricultural AI field, containing 100,000 standardized images, covering 139 crops widely grown around the world. The crop types covered include food crops (such as rice, wheat, and corn), cash crops (such as cotton, soybeans, and rapeseed), vegetables (such as tomatoes, cucumbers, and cabbages), and fruits (such as apples, grapes, and bananas).

This dataset covers multiple growth stages of crops from seedlings to flowering and fruiting, and the image content covers multiple structural parts such as leaves, stems, and fruits, with rich representation information. All images are unified into 224×224 pixels to reduce the impact of size differences on model training, and support RGB, BGR, and GRAY color formats to adapt to the input requirements of different computer vision algorithms.