Plant Disease Detection and Care Recommendation System Using Computer Vision and Deep Learning

A computer vision system that detects plant diseases from leaf photographs and recommends care and treatment steps.

A computer vision system that detects plant diseases from leaf photographs and recommends care and treatment steps. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to work with images or video: building a dataset, training or fine-tuning a vision model, measuring its performance and wrapping it in a usable tool.

The main parts are personalised recommendations ranked by relevance, dataset preparation and annotation, model training or fine-tuning, evaluation with standard metrics, plus visual examples, and an interface that works on uploaded images or live video. The reference build uses Python, OpenCV, PyTorch, and NumPy, with a clear project structure, setup instructions and sample data so that it can be run and extended.