This project focuses on leveraging Convolutional Neural Networks (CNN) to classify diseases affecting eggplants. By utilizing deep learning techniques, this solution aims to provide a robust mechanism for early detection and classification of various eggplant diseases based on input images. The repository includes training scripts, dataset information, and model evaluation tools.

• Dataset preparation: Information and scripts for preparing the dataset for training.
• Model training: Scripts for training CNN models on the prepared dataset.
• Evaluation: Tools and scripts for evaluating model performance and analyzing results.
• Requirements: Details on the required libraries and dependencies to run the code.

1. Clone the repository: git clone https://github.com/syedissambukhari/Eggplant-disease-Classification-using-CNN.git

2. Prepare the dataset following the instructions in the data_preparation directory.

3. Train the CNN model using the scripts provided in the model_training directory.

4. Evaluate the trained models using the evaluation tools available in the repository.

5. Refer to the documentation for detailed instructions on each step and additional customization options.

Contributions to this project are welcome! If you find any bugs or have suggestions for improvements, please feel free to open an issue or submit a pull request.

This project is licensed under the MIT License - see the LICENSE file for details.