OpenCV Explorer

A versatile application for exploring OpenCV filters and transformations using your webcam, available with Streamlit web interface, Tkinter desktop interface, and a modern PySide6 (Qt6) desktop interface.

Features

• Real-time video processing with WebRTC (Streamlit), native camera capture (Tkinter), and Qt6 (PySide6)
• Multiple image filters and transformations
• Hand tracking and face mesh detection with MediaPipe
• Support for both local development and cloud deployment
• ArUco marker detection with multiple dictionary options
• Easy-to-use UI with adjustable parameters for each filter
• Modern Qt6 interface with collapsible sections, smooth animations, and a beautiful dark theme

Filters and Transformations

• Color filtering with HSV controls
• Edge detection with Canny algorithm
• Gaussian blur with adjustable kernel size
• Image rotation
• Image resizing
• Contour detection
• Histogram equalization
• Adaptive thresholding
• Morphological operations (erosion, dilation, opening, closing)
• Sharpening
• Hough line detection
• Hough circle detection
• Optical flow visualization
• Pencil sketch effect
• Color quantization
• Stylization effect
• Cartoonify effect
• Hand tracking with MediaPipe
• Face mesh tracking with MediaPipe
• ArUco marker detection with multiple dictionary options

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/OpenCVGUI.git
   cd OpenCVGUI

2. Install dependencies:

   pip install -r requirements.txt

Usage

PySide6 (Qt6) Desktop Interface (Recommended)

Run the modern Qt6 interface:

python run.py -i pyside6

Or using the alias:

python run.py -i qt

Or directly:

python src/pyside6_app.py

The PySide6 interface features:

• Modern dark theme with teal accents
• Collapsible filter sections for better organization
• Smooth slider controls with real-time value display
• Responsive layout with adjustable splitter
• High-performance video rendering

Streamlit Web Interface

Run the application with Streamlit:

python run.py -i streamlit

Or directly:

streamlit run src/streamlit_app.py

Tkinter Desktop Interface

Run the application with Tkinter:

python run.py -i tkinter

Or directly:

python src/tkinter_app.py

Deployment to Streamlit Cloud

When deploying to Streamlit Cloud, you need to configure a TURN server to ensure WebRTC connections work properly. This application uses Twilio's TURN server service. Follow these steps:

1. Create a free Twilio account at https://www.twilio.com/try-twilio
2. Once you have your account, go to your Twilio Console dashboard
3. Find your Account SID and Auth Token
4. Set these values as secrets in your Streamlit Cloud deployment:
   • Go to your app settings in Streamlit Cloud
   • Add two secrets:
     • TWILIO_ACCOUNT_SID with your Account SID value
     • TWILIO_AUTH_TOKEN with your Auth Token value

Twilio offers a free trial with a certain amount of credit, which should be sufficient for testing and moderate usage.

How It Works

The application captures video from your webcam and applies various OpenCV transformations in real-time based on your selections. The processing is sequential, meaning the order of operations matters - each operation is applied to the result of the previous one.

Streamlit Interface

The WebRTC component ensures low-latency video streaming in the browser, making the transformations appear in real-time.

Tkinter Interface

The native desktop interface provides direct access to your webcam with minimal latency, perfect for testing OpenCV functions locally.

ArUco Marker Detection

The application includes support for detecting ArUco markers, which are useful for augmented reality, camera calibration, and pose estimation. You can select from multiple ArUco dictionaries:

• 4x4 markers (50, 100, 250, 1000 markers)
• 5x5 markers (50, 100, 250, 1000 markers)
• 6x6 markers (50, 100, 250, 1000 markers)
• 7x7 markers (50, 100, 250, 1000 markers)
• Original ArUco markers

Troubleshooting

• If you encounter connection issues on Streamlit Cloud, check that your Twilio credentials are correctly set up.
• If the webcam doesn't start, ensure your browser has permission to access the camera.
• Some browsers or networks may have restrictive policies that block WebRTC connections. Try a different browser or network if you encounter issues.
• For Tkinter interface, press 'q' to exit the application.
• For PySide6 interface, close the window normally or press Ctrl+Q to exit.
• If PySide6 fails to start, ensure you have Qt6 libraries installed: pip install PySide6

License

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