Image Classification with CNN

This project demonstrates the use of Convolutional Neural Networks (CNN) for image classification using the CIFAR-10 dataset.

Table of Contents

• Installation
• Usage
• Results
• Contributing
• License

Installation

1. Clone the repository:

   git clone https://github.com/anton1osdotcom/image-classification-cnn.git

2. Navigate to the directory:

   cd image-classification-cnn

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Training the Model:

   python3 src/train.py

2. Evaluating the Model:

   python3 src/evaluate.py

3. Plotting the Results:

   python3 src/plot_history.py

Results

• The model achieved an accuracy of approximately 70% on the CIFAR-10 test dataset.
• Confusion matrix and accuracy/loss plots can be found in the results/ directory.

Contributing

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Open a Pull Request.

License

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