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Object Scope — Browser-Based Real-Time Object Detection with TensorFlow.js #8745
Description
Activity
Hi @fouad-salehi,
This is a great demonstration of real-time object detection in the browser using TensorFlow.js and COCO-SSD. Thanks for sharing your project and seeking feedback from the community.
Please continue to share your findings and improvements.Reacted by Fouad SalehiHi @fouad-salehi,
This is a great demonstration of real-time object detection in the browser using TensorFlow.js and COCO-SSD. Thanks for sharing your project and seeking feedback from the community. Please continue to share your findings and improvements.
Thank you, @nileshau-afk! I really appreciate your kind feedback and for taking the time to check out Object Scope. I’ll keep improving the project and sharing future updates with the TensorFlow.js community.
Hi @fouad-salehi,
Thank you for opening this issue. We are closing this issue for now.
You would like to work on it, please feel free to reopen the issue or submit a pull request referencing it.Thank you for your understanding.
Hello TensorFlow.js community,
I would like to share Object Scope, a browser-based computer vision project built with TensorFlow.js and COCO-SSD.
Live Demo: https://objectscope-research.web.app/
Source Code: https://github.com/fouad-salehi/objectScope
What is Object Scope?
Object Scope demonstrates real-time and image-based object detection directly in the web browser, without requiring a dedicated backend for inference.
It currently provides two main modes:
Image Detection — Upload an image and detect objects.
Camera Detection — Use a live camera stream for real-time object detection.
The application displays detected objects with bounding boxes and confidence scores.
Technology
TensorFlow.js
COCO-SSD
JavaScript
HTML5 / CSS3
Firebase Hosting
Why I'm sharing it
The goal of this project is to explore the practical use of TensorFlow.js for computer vision applications running entirely in the browser.
I would appreciate feedback from the TensorFlow.js community regarding:
Real-time detection performance
Browser compatibility
Model loading and inference performance
Potential improvements to the TensorFlow.js implementation
Suggestions for future development
If you have a few minutes, you can try the live demo directly in your browser and share your feedback.
Thank you to the TensorFlow.js team and community for the tools that made this project possible.