This repository demonstrates how to use ONNX Runtime to run Yolov8-seg models in the browser, including support for batched image processing. The example application displays several images and applies the Yolov8-seg model to detect objects and segment them, with results displayed directly on the webpage.
- Object Detection: Detects various objects in images using YOLOv8.
- Segmentation: Provides segmentation masks for specific objects like persons.
- Real-time Processing: Processes images in real-time directly in the web browser.
- Interactive Gallery: Displays processed images with interactive hover effects.
- ONNX Runtime: For running the YOLOv8 and segmentation models.
- TensorFlow.js: For image preprocessing and manipulation.
- OpenCV.js: Used for drawing masks.
- HTML/CSS/JavaScript: Frontend development technologies.
This image shows the state before segmentation.
This image shows the segmentation results of the web application.
Simply clone the repository and open index.html in live server in a web browser .
git clone https://github.com/shimaamorsy/ONNX_Runtime_Web_Yolov8-seg_Batching.git