qontinui-api 0.1.1

REST API service for Qontinui GUI automation

Qontinui API Service

REST API service that exposes real qontinui library image recognition capabilities for web-based testing.

Features

• Real Qontinui Pattern Matching: Uses actual qontinui Find operations
• State Detection: Detect which states are present in screenshots
• Location Validation: Validate locations with image-relative positioning
• Web-Friendly: Base64 image support for easy browser integration

Endpoints

Vision Operations

POST /find

Find a single template match in a screenshot using qontinui's real pattern matching.

{
  "screenshot": "base64_image_data",
  "template": "base64_image_data",
  "similarity": 0.8,
  "search_region": {"x": 0, "y": 0, "width": 100, "height": 100}
}

POST /find_all

Find all template matches in a screenshot.

POST /detect_states

Detect which states from a list are present in a screenshot.

{
  "screenshot": "base64_image_data",
  "states": [...],
  "similarity": 0.8
}

POST /validate_location

Validate if a location is accessible, with optional image-relative positioning.

Installation

1. Install Python dependencies:

pip install -r requirements.txt

2. Start the service:

./start.sh

Or manually:

uvicorn main:app --reload --host 0.0.0.0 --port 8000

API Documentation

When running, interactive API documentation is available at:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Integration with Frontend

The API accepts base64-encoded images and returns JSON responses with match regions, scores, and detection results. Perfect for integration with the qontinui-web frontend for visual testing and validation.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Please note that this project is released with a Code of Conduct. By participating in this project you agree to abide by its terms.

License

This project is open source. See the LICENSE file for details.

Contact

For questions or issues, please contact [e-mail] or open an issue on GitHub.