CNN Project: Cat vs Dog Image Classification

Welcome to the Cat vs Dog Image Classification project! This repository contains a project demonstrating the use of Convolutional Neural Networks (CNNs) to classify images as either a cat or a dog.

Table of Contents

• Project Overview
• Requirements
• Installation
• Contributing

Project Overview

This project focuses on building a CNN model to classify images into two categories: cats and dogs. We use TensorFlow and Keras to train a deep neural network on a dataset of labeled images.

• Technologies Used: TensorFlow, Keras
• Dataset: Kaggle Cats and Dogs Dataset
• Key Features: Data preprocessing, model training, evaluation, and inference.

Requirements

To run this project, you'll need the following dependencies:

• Python 3.7+
• TensorFlow
• Keras
• NumPy
• Matplotlib

Installation

1. Clone the repository:

   git clone https://github.com/NicolasIDias/Convolutional-neural-network.git
   cd Convolutional-neural-network

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Contributing

Contributions are welcome! If you have any suggestions, bug reports, or pull requests, please feel free to submit them.

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

License

This repository is licensed under the MIT License. See the LICENSE file for more information.