Image Playground is an interactive Streamlit application that offers a comprehensive suite of image processing, computer vision, and AI-powered tools. From simple filters to advanced deep learning capabilities, this app provides both fun and educational ways to explore digital imaging techniques.
- Photo Booth: Apply fun and advanced effects to webcam captures
- Meme Factory: Create custom memes with your own images
- Filtering Arcade: Apply various image filters with real-time previews
- AI Art Studio: Generate images using Stable Diffusion (when connected)
- Histogram Analysis: Visualize and manipulate image histograms
- Edge Detection: Explore feature detection algorithms
- Fourier Transforms: Visualize images in the frequency domain
- Image Segmentation: Try different segmentation techniques
- Shape Analysis: Detect and analyze shapes in images
- Object Detection: Identify objects using YOLO v8
Track your progress through various challenges including:
- First Upload
- Selfie Master
- Meme Genius
- Filter King
- AI Explorer
- Python 3.8+
- Pip package manager
- Clone this repository:
git clone https://github.com/yourusername/image-playground.git
cd image-playground- Install the required packages:
pip install -r requirements.txt- Run the app:
streamlit run app.pyFor the AI Art Studio functionality, you need a running instance of Stable Diffusion with API access:
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
cd stable-diffusion-webui
python launch.py --apigit clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
python main.pyThe app will automatically detect a running Stable Diffusion instance at http://127.0.0.1:7860 by default.
After starting the app, navigate to the different pages using the sidebar menu:
- Welcome: View your achievements and get started
- Photo Booth 🎮: Capture images from your webcam and apply filters
- Meme Factory 😂: Create custom memes with text overlays
- Image Digitization: Explore pixel-level image properties
- Histogram & Metrics: Analyze image histograms and statistics
- Filtering & Enhancements: Apply various image filters
- Edge Detection & Features: Detect edges and extract features
- Transforms & Frequency Domain: Visualize Fourier transforms
- Image Restoration: Simulate and fix image degradation
- Segmentation & Representation: Segment images using various techniques
- Shape Analysis: Detect and analyze shapes in images
- Object Detection 🔍: Identify objects using YOLO v8
- AI Art Studio 🎨: Generate images with Stable Diffusion
- Streamlit: For the interactive web interface
- OpenCV: For core image processing functionality
- NumPy: For numerical operations
- Matplotlib: For plotting and visualization
- Pillow: For image manipulation
- Scikit-image: For additional image processing algorithms
- Ultralytics & Supervision: For YOLO object detection
-
Missing Dependencies:
- Ensure all requirements are installed using
pip install -r requirements.txt - For GPU acceleration, make sure compatible CUDA drivers are installed
- Ensure all requirements are installed using
-
Webcam Access:
- Browser permissions must allow webcam access
- Check that no other applications are using your camera
-
Stable Diffusion Connection:
- Ensure Stable Diffusion is running with the
--apiflag - Check the API URL in the sidebar (default is http://127.0.0.1:7860)
- For VRAM issues, try models that require less memory
- Ensure Stable Diffusion is running with the
-
Object Detection Issues:
- The app will download the YOLO model on first use
- Ensure you have internet access for the initial download
- For slower computers, avoid using high-resolution images
- Close other resource-intensive applications
- For AI Art generation, lower image dimensions for faster results
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Streamlit for the amazing web app framework
- OpenCV and related libraries for image processing capabilities
- Ultralytics for YOLO implementation
- Stable Diffusion for AI image generation
- All contributors and testers who have helped improve this app
Note: This application is designed for educational purposes to demonstrate various image processing and computer vision techniques. Some features like AI Art Studio require additional setup of external services.