Image Identification System 📷

A simple web-based image identification application using Streamlit and MobileNetV2. This project utilizes a pre-trained convolutional neural network to classify images into various categories, providing predictions along with confidence scores.

Features ✨

• Image upload and classification
• Top-5 predictions with confidence scores
• User-friendly interface with real-time feedback
• Efficient loading with model caching

Tech Stack 🛠️

• Python (Core Logic)
• Streamlit (Frontend)
• TensorFlow (Model)
• OpenCV (Image Processing)
• PIL (Image Handling)

Installation 💻

Clone the repository and install the required packages:

# Clone the repo
git clone https://github.com/Galaxicitti/image-identification-system.git
cd image-identification-system

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

# Install required packages
pip install -r requirements.txt

requirements.txt:

streamlit
tensorflow
opencv-python
pillow

Usage 🚀

Run the application with the following command:

streamlit run main.py

Open the displayed URL in your browser to access the app.

File Structure 📂

Image Identification System/
│
├── main.py               # Main application code
├── requirements.txt      # Python dependencies
└── README.md             # Project documentation

Future Improvements 🌱

• Add image heatmaps for better interpretability
• Include support for batch processing
• Integrate custom models for specialized tasks
• Add mobile support for better responsiveness

License 📄

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

Contributing 🤝

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

Contact 📬

Feel free to reach out via LinkedIn or GitHub.