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Hacktoberfest 2023 Project

Welcome to our Hacktoberfest 2023 project! We're excited to have you contribute. This project aims to [briefly describe the goal or purpose of the project].

#hacktoberfest

Cat-Dog Classification Project

Overview

This project aims to classify images as either a cat or a dog using machine learning techniques. The model has been trained on a dataset of cat and dog images to make predictions on new, unseen data.

Getting Started

Follow these instructions to set up the project on your local machine.

Prerequisites

  • Python 3.x
  • Pip (Python package installer)

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/cat-dog-classification.git
  2. Navigate to the project directory:

    cd cat-dog-classification
  3. Install the required dependencies:

    pip install -r requirements.txt

Usage

  1. Data Preparation:

    • Place your cat and dog images in the data directory.
    • Ensure that the images are organized into subdirectories, such as data/train/cat, data/train/dog, data/test/cat, and data/test/dog.
  2. Training:

    • Run the training script to train the model:

      python train.py
    • Adjust hyperparameters in the config.yaml file as needed.

  3. Prediction:

    • Use the trained model to make predictions on new images:

      python predict.py --image_path path/to/your/image.jpg
  4. Evaluate:

    • Evaluate the model performance on a test dataset:

      python evaluate.py

Contributing

If you would like to contribute to the project, follow these steps:

  1. Fork the repository.

  2. Create a new branch for your feature or bug fix:

    git checkout -b feature/your-feature-name
  3. Make your changes and commit them:

    git commit -m "Description of your changes"
  4. Push your changes to your fork:

    git push origin feature/your-feature-name
  5. Open a pull request on the original repository.

License

This project is licensed under the MIT License.