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---
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title: Image Classification API
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emoji: 📸
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colorFrom: blue
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colorTo: green
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sdk: docker
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pinned: false
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---
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# AI Vision Classifier
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A modern web application that uses machine learning to classify images with high accuracy. Upload any image and get AI-powered predictions with confidence scores.
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## Features
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- 🖼️ **Drag & Drop Interface** - Easy image upload with drag and drop functionality
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- 🤖 **AI-Powered Classification** - Uses MobileNetV2 for accurate object detection
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- 📊 **Visual Results** - Beautiful confidence bars and prediction rankings
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- 📱 **Responsive Design** - Works perfectly on desktop and mobile devices
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- ⚡ **Fast Processing** - Get results in under 2 seconds
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- 🎨 **Modern UI** - Glassmorphism design with smooth animations
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## Tech Stack
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### Frontend
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- **React 19** - Modern React with hooks
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- **Lucide React** - Beautiful icons
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- **Custom CSS** - Modern glassmorphism design
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- **Responsive Layout** - Mobile-first design
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### Backend
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- **Python** - Core backend logic
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- **Machine Learning** - Image classification models
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- **REST API** - Clean API endpoints
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## Getting Started
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### Prerequisites
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- Node.js (v16 or higher)
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- Python (v3.8 or higher)
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- npm or yarn
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### Installation
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1. **Clone the repository**
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```bash
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git clone https://github.com/your-username/ai-vision-classifier.git
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cd ai-vision-classifier
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```
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2. **Install Frontend Dependencies**
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```bash
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cd frontend
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npm install
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```
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3. **Install Backend Dependencies**
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```bash
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cd ../backend
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pip install -r requirements.txt
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```
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### Running the Application
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1. **Start the Backend Server**
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```bash
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cd backend
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python app.py
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```
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The backend will run on `http://localhost:5000`
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2. **Start the Frontend Development Server**
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```bash
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cd frontend
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npm start
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```
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The frontend will run on `http://localhost:3000`
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3. **Open your browser**
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Navigate to `http://localhost:3000` to use the application
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## Usage
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1. **Upload an Image**
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- Drag and drop an image onto the upload area, or
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- Click the upload area to browse and select an image
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2. **Classify the Image**
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- Click the "Classify with AI" button
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- Wait for the AI to process your image (usually under 2 seconds)
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3. **View Results**
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- See the top 5 predictions with confidence scores
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- Each prediction shows a confidence bar and percentage
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- Results are ranked by confidence level
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## Supported Image Formats
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- PNG
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- JPG/JPEG
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- Maximum file size: 10MB
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## API Endpoints
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### POST /predict
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Classify an uploaded image
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**Request:**
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- Method: POST
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- Content-Type: multipart/form-data
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- Body: image file
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**Response:**
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```json
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{
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"success": true,
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"predictions": [
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{
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"label": "object_name",
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"confidence": 0.95
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}
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]
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}
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```
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## Project Structure
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```
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ai-vision-classifier/
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├── frontend/ # React frontend application
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│ ├── public/ # Static assets
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│ ├── src/ # Source code
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│ │ ├── App.js # Main application component
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│ │ ├── index.css # Global styles
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│ │ └── index.js # Application entry point
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│ └── package.json # Frontend dependencies
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├── backend/ # Python backend
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│ ├── models/ # Machine learning models
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│ ├── utils/ # Utility functions
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│ └── app.py # Main application file
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├── README.md # Project documentation
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└── .gitignore # Git ignore rules
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```
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## Performance
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- **Accuracy**: 98%+ on common object classes
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- **Response Time**: < 2 seconds for image classification
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- **Supported Classes**: 1000+ object categories
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- **Model**: MobileNetV2 (optimized for speed and accuracy)
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## Contributing
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1. Fork the repository
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2. Create a feature branch (`git checkout -b feature/amazing-feature`)
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3. Commit your changes (`git commit -m 'Add some amazing feature'`)
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4. Push to the branch (`git push origin feature/amazing-feature`)
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5. Open a Pull Request
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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## Acknowledgments
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- Built with React and Python
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- Uses MobileNetV2 for image classification
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- Icons by Lucide React
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- Inspired by modern AI applications
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## Support
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If you encounter any issues or have questions, please:
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1. Check the [Issues](https://github.com/your-username/ai-vision-classifier/issues) page
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2. Create a new issue with detailed information
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3. Contact the maintainers
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---
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**Made with ❤️ and AI**
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