This project predicts plant diseases based on an input image of a plant or leaf. The system uses a machine learning model to identify diseases and provides:

The name of the disease.

A description of how the disease occurs.

Suggestions on how to prevent or treat the disease.

The project is a prototype created for academic purposes to demonstrate the application of computer vision in agriculture.

The system can predict the following plant diseases:

Apple___Apple_scab

Apple___Black_rot

Apple___Cedar_apple_rust

Apple___healthy

Blueberry___healthy

Cherry_(including_sour)__Powdery_mildew

Cherry_(including_sour)___healthy

Corn_(maize)__Cercospora_leaf_spot Gray_leaf_spot

Corn_(maize)_Common_rust

Corn_(maize)__Northern_Leaf_Blight

Corn_(maize)___healthy

Grape___Black_rot

Grape___Esca_(Black_Measles)

Grape___Leaf_blight_(Isariopsis_Leaf_Spot)

Grape___healthy

Orange___Haunglongbing_(Citrus_greening)

Peach___Bacterial_spot

Peach___healthy

Pepper,_bell___Bacterial_spot

Pepper,_bell___healthy

Potato___Early_blight

Potato___Late_blight

Potato___healthy

Raspberry___healthy

Soybean___healthy

Squash___Powdery_mildew

Strawberry___Leaf_scorch

Strawberry___healthy

Tomato___Bacterial_spot

Tomato___Early_blight

Tomato___Late_blight

Tomato___Leaf_Mold

Tomato___Septoria_leaf_spot

Tomato___Spider_mites_Two-spotted_spider_mite

Tomato___Target_Spot

Tomato___Tomato_Yellow_Leaf_Curl_Virus

Tomato___Tomato_mosaic_virus

Tomato___healthy

Anaconda Environment with Python 3.10 version

Required Libraries: All dependencies are specified in the requirements.txt file.

Create a Conda environment with Python 3.10:

Activate the Conda environment:

Install the required dependencies:

Run the Flask application:

The dataset used for training the model is available on Kaggle. It contains images of various plants and their respective diseases, enabling the model to accurately identify diseases based on image input.

Dataset source: New Plant Diseases Dataset on Kaggle

Model: The model used in this project is based on PyTorch ResNet, a widely used deep learning architecture for image classification tasks.

Dataset: New Plant Diseases Dataset on Kaggle.

This project was created for academic purposes to demonstrate plant disease prediction using machine learning and Flask.

This project is for academic purposes only. The PyTorch ResNet model has been used as the foundation for disease prediction and is credited to the PyTorch development team and contributors. Use of this project for commercial purposes is not permitted without proper permissions.