Potato Leaf Disease Detector

Potato Leaf Disease Detector

A Python-based machine learning project designed to identify diseases in potato leaves from images. The system uses computer vision and deep learning techniques to accurately classify leaves into healthy or diseased categories.

Key Features:

Image-based detection: Users can upload a photo of a potato leaf, and the system analyzes it.

High accuracy: Uses advanced machine learning algorithms to correctly identify multiple leaf disease types.

Python & OpenCV implementation: Core logic implemented in Python, leveraging image processing libraries for pre-processing and feature extraction.

User-friendly interface: Simple interface for farmers or agronomists to quickly detect leaf diseases.

Technologies Used: Python, OpenCV, TensorFlow/Keras (or Scikit-Learn if you used that), and possibly GUI libraries if you made one.

Impact: Helps in early detection of potato leaf diseases, reducing crop losses and improving yield.