Potato Leaf Disease Identification using Deep Learning

This repository contains a Python application for detecting potato leaf diseases using a pre-trained deep learning model. The application uses PyQt5 for the GUI and TensorFlow for model inference.

Requirements

• Python 3.11.6
• PyQt5
• Pillow
• NumPy
• TensorFlow

Note: This code is designed to run without errors only in Python 3.11.6 version.

Installation

1. Install the required packages:

   pip install PyQt5 Pillow numpy tensorflow

2. Download the pre-trained model here and place potato_leaf_disease_model.h5 in the project directory.

Usage

1. Ensure that the pre-trained model potato_leaf_disease_model.h5 is in the project directory.

2. Run the application:

   python app.py

3. Use the GUI to select an image of a potato leaf and detect the disease.

Dataset

The dataset used for training the model can be downloaded from here.

Pre-trained Models (required)

The pre-trained model used for this application can be downloaded from this link.

Model Training (optional)

Training the model is optional. The application comes with a pre-trained model, but if you wish to train the model yourself, follow these steps:

1. Download and extract the dataset from Kaggle.

2. Update the paths in model_training.py to point to your dataset directories.

3. Run the training script:

   python Model Training Code.py

4. The trained model will be saved as potato_leaf.h5.