Description

Crop type classification using machine learning in Python is a powerful technique that leverages advanced algorithms and remote sensing data to accurately identify and categorize different types of crops within agricultural landscapes. By extracting valuable features from satellite imagery or drone footage, machine learning models can distinguish between crops such as corn, wheat, and soybeans with high precision. This technology not only aids farmers in optimizing resource allocation but also plays a crucial role in monitoring crop health and predicting yields, ultimately contributing to more efficient and sustainable agricultural practices. The process is proposed and implemented image processing technique using OpenCV for separating the diseased part of the crop from the image of the crop. Foreground Extraction, Feature extraction and classification is done for crop images