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web-vision-detect

Detect and classify objects in web applications using YOLOX on ONNX Runtime Web.

Updated Jul 5, 2026
Search Tags:#web application#object recognition#real-time object detection#YOLOX#ONNX Runtime Web
One-click install
npx skills add https://github.com/prince3626ezechiel-lang/ivoire-monade-palantir --skill web-vision-detect
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: web-vision-detect
Source: https://github.com/prince3626ezechiel-lang/ivoire-monade-palantir/tree/main/skills/web-vision-detect
Command: npx skills add https://github.com/prince3626ezechiel-lang/ivoire-monade-palantir --skill web-vision-detect

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill offers real-time object detection within web applications, allowing for the identification, labeling, and counting of objects from live camera feeds or static images.

Core Features & Use Cases

  • Real-time Object Detection: Detect and classify objects in real-time using YOLOX and ONNX Runtime Web.
  • On-Device Processing: Ensures no data leaves the device, providing a secure, on-device experience.
  • Custom Models: Support for custom-trained YOLO/YOLOX models, enabling tailored detections.
  • Use Case: A retail store uses this Skill to automatically count and identify products on shelves, enhancing inventory management.

Quick Start

Add the web-vision-detect kit to your project to start object detection.

Frequently Asked Questions about web-vision-detect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run real-time object detection in a web application without a backend server?▼

Real-time object detection in web applications can be achieved using YOLOX on ONNX Runtime Web. This approach processes live camera feeds or static images directly on-device, eliminating the need for server infrastructure while maintaining data privacy.

Can I use custom YOLO models for object detection with ONNX Runtime Web?▼

Custom YOLO models can be deployed for object detection with ONNX Runtime Web. The skill supports custom-trained YOLO and YOLOX models, enabling tailored detection and classification of specific objects directly within the browser environment.

Does on-device object recognition in web apps ensure data privacy for live camera feeds?▼

On-device object recognition ensures complete data privacy for live camera feeds. By leveraging ONNX Runtime Web, all detection and classification processing happens locally in the browser, ensuring no data leaves the device.

What is the best way to count and label products on shelves using a web interface?▼

Counting and labeling products on shelves via a web interface is best handled by real-time object detection using YOLOX. This on-device approach automatically identifies and tallies retail inventory items from live video feeds.

How to classify objects from static images directly in the browser?▼

Classifying objects from static images directly in the browser requires running YOLOX on ONNX Runtime Web. This setup performs real-time object detection and labeling locally without transmitting image data to external servers.

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