Description

This PR introduces the JSONSink class to address structured logging of object detection data into JSON format, as requested in issue #748. The class supports logging of bounding boxes, class IDs, confidence scores, and frame numbers, enhancing post-processing data analysis and interpretability.

The PR includes:

• JSONSink class implementation.
• Comprehensive unit tests for the class.
• A demo showcasing the integration of JSONSink with a video processing pipeline.

Note: The JSONSink class was placed directly in the utils folder in the file.py file due to its capability to handle various types of file operations integral to the project's core functionality. Open to suggestions if there's a more appropriate location within the project structure.

Type of Change

• New feature: Added JSONSink class for structured logging of detection data.

Testing

The JSONSink class was validated through a series of unit tests, covering:

• Logging with various custom data scenarios.
• Handling of scenarios with no detections.
• Verification of JSON output format and data integrity.

A demo script demonstrates the class's usage within a video processing workflow, annotating video frames and logging detections to a JSON file. Demo Here

Documentation Updates

• Added JSONSink class documentation within the module, detailing its purpose, usage, and example usage.
• Updated README to include a section on structured detection data logging, introducing the JSONSink class.