Plant_Disease_Detection

Crop diseases are a significant threat to food security, but their rapid identification remains difficult in many parts of the world due to a lack of necessary infrastructure. Detecting plant diseases is crucial for every farmer, so we have developed a plant disease detection system using deep learning. In this system, we utilize Convolutional Neural Networks (CNNs) to classify leaf images into 39 different categories.

Dataset link

https://data.mendeley.com/datasets/tywbtsjrjv/1

Pre-trained model using cnn

Download the pretrained model from the below link : https://drive.google.com/file/d/1b1ZHVNuWLxC1aWH7PO9-mwql0Q3306kl/view?usp=drive_link

Screenshot

Description

1. Train the model using CNN in jupyter notebook.
2. Save the model as .pt file or else use the pre-trained model.
3. paste the.pt file in the Flask Depolyed App folder.
4. Then run the Flask Depolyed App folder using python App.py command in visual studio.
5. The desired web page will be opened , upload the test images which has been already uploaded.
6. The diseased leaves with its description and supplements will be displayed.