# 🐾 Animal Detector 🐾

Welcome to the Animal Detector project! This repository contains code and resources for training a machine learning model to recognize 15 different animal classes and classify images accordingly. 

## 🦁 About the Project

This project uses a Convolutional Neural Network (CNN) to identify the following animals:
- Bear
- Bird
- Cat
- Cow
- Deer
- Dog
- Dolphin
- Elephant
- Giraffe
- Horse
- Kangaroo
- Lion
- Panda
- Tiger
- Zebra

The model is trained on images stored in the `animal_data` directory, and can classify new images provided by the user.

## 📁 Project Structure


Animal-Detector/
├── animal_data/
│   ├── Bear/
│   ├── Bird/
│   ├── Cat/
│   └── ... (other animal folders)
├── Animal-Detector.py
├── Animal-Detector-model.py
├── bear-1.jpg
├── README.md
└── requirements.txt


- `animal_data/`: Contains subdirectories for each animal class with training images.
- `Animal-Detector.py`: Script to classify a new image.
- `Animal-Detector-model.py`: Script to train and save the model.
- `bear-1.jpg`: Sample image for testing.
- `README.md`: Project documentation.
- `requirements.txt`: List of required Python packages.

## 🚀 Getting Started

### Prerequisites

Ensure you have Python installed along with the necessary packages:
```sh
pip install -r requirements.txt

Training the Model

To train the model, run:

python Animal-Detector-model.py

This will train the CNN on the images in animal_data/ and save the trained model as animal_classifier_model.h5.

Classifying Images

To classify a new image, use:

python Animal-Detector.py path_to_your_image.jpg

Replace path_to_your_image.jpg with the path to the image you want to classify. The script will output the predicted animal class and confidence level.

🐍 Example Usage

Here's an example of how to use the classifier with the provided bear-1.jpg image:

python Animal-Detector.py bear-1.jpg

Sample Output

This image is a Bear with 98.76% confidence.

📜 License

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

🙌 Acknowledgements

• Inspired by the need to classify and detect animals using machine learning.
• Thanks to the TensorFlow and Keras communities for their excellent resources and support.

🤝 Contributing

Feel free to fork this repository and make improvements. Pull requests are welcome!

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🔗 Author: Armanx200

This README includes emojis, a clear structure, and detailed instructions to make the project easy to understand and use.