jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI
A PyQt-based GUI application for YOLO-powered object detection, tracking, pose estimation, and segmentation.
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This repository provides a desktop application built with PyQt5 that wraps Ultralytics YOLO models for computer vision tasks. It supports detection, pose estimation, and instance segmentation using YOLO11, YOLOv13, and YOLOv8 variants across multiple model sizes. The application uses DeepSort and ByteTrack algorithms for multi-object tracking and runs inference via ONNX Runtime. Users can process local images, videos, camera feeds, or RTSP streams through the graphical interface.
Frequently asked
- What is jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI?
- A PyQt-based GUI application for YOLO-powered object detection, tracking, pose estimation, and segmentation.
- Is ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI open source?
- Yes — jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI is open source, released under the MIT license.
- What language is ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI written in?
- jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI is primarily written in Python.
- How popular is ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI?
- jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI has 453 stars on GitHub.
- Where can I find ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI?
- jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI is on GitHub at https://github.com/jingh-ai/ultralytics-YOLO-DeepSort-ByteTrack-PyQt-GUI.