ImageNet-Classifier

A lightweight and user-friendly image classification tool powered by MobileNet pre-trained on ImageNet. This project provides a simple interface to classify images with beautiful result displays.

📋 Features

• Pre-trained MobileNet Model: Utilizes the MobileNet architecture pre-trained on ImageNet for efficient image classification
• Beautiful UI: Displays prediction results in an aesthetically pleasing gradient card
• Simple Integration: Easily incorporate into existing Jupyter notebooks or Python applications
• Fast Performance: Optimized for quick predictions on standard hardware

🛠️ Installation

# Clone the repository
git clone https://github.com/yourusername/imagenet-classifier.git
cd imagenet-classifier

# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

📊 Dependencies

This project requires the following Python packages:

• TensorFlow
• NumPy
• Matplotlib
• Pillow (PIL)
• IPython
• ipywidgets

Results

Fig 1: Cat Image Classification Result

Fig 2: Sunflower Image Classification Result

Full API

• The project provides three main functions:

preprocess_image(path)

• Loads, resizes, and preprocesses an image for MobileNet input.

predict_image_class(img_array)

• Uses MobileNet to classify the preprocessed image and returns a formatted prediction string.

show_prediction_result(label)

• Displays the prediction result in a beautiful gradient card with interactive buttons.

🛣️ Roadmap

1. Add support for image upload via URL
2. Implement batch processing for multiple images
3. Create a standalone web application version
4. Add more visualization options for prediction confidence

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

📜 License

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

🙏 Acknowledgements

• TensorFlow for the amazing deep learning framework
• MobileNet architecture developers
• ImageNet for the dataset used in pre-training

Made with ❤️ by Humaima Anwar