DEVELOPMENT OF AI BASED MODEL FOR PLANT DISEASE DETECTION

Computer Engineering

This project provides an innovative method for detecting plant diseases that leverages the power of ReactJS for the front-end interface and Flask for the back-end, backed up by a powerful deep learning model based on ResNet architecture. Our dataset collection contains over 20,600 high-resolution photos of diverse plant types and illnesses. Pretrained on this massive dataset, the deep learning model employs the cutting-edge ResNet architecture to achieve precise and reliable plant disease categorization across a wide range of plant kinds. This method is a vital tool for farmers, agricultural specialists, and researchers, allowing for speedy and precise plant disease identification, resulting in increased crop output and global food security. We also made a web application for the above AI model which will expect an image and detect it against diseases and provides result with coordinates, confidence, etc. The web application is mainly made with React js and Flask, which will be a very good addition to the user experience. In summary, we are creating a plant disease detection application using ReactJS, Flask, and deep learning model (ResNet50) to achieve precise and reliable plant disease categorization.

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