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Depth Anything Large Hf

Developed by Xenova
ONNX version of depth estimation model based on Transformers.js, suitable for web applications
Downloads 19
Release Time : 1/24/2024

Model Overview

This model is the ONNX format version of Depth Anything Large, specifically designed for monocular depth estimation tasks, capable of predicting scene depth information from a single RGB image.

Model Features

Web Optimization
Converted to ONNX format and adapted to Transformers.js, can run directly in browsers
Monocular Depth Estimation
Only requires a single RGB image to predict scene depth information
Lightweight Deployment
Suitable for front-end application integration, no complex backend service required

Model Capabilities

Single-image depth estimation
Scene depth map generation
Real-time inference on web

Use Cases

Computer Vision
3D Scene Reconstruction
Generate depth information from 2D images for 3D scene construction
Can output high-precision depth maps
Augmented Reality Applications
Provide scene depth information for AR applications
Achieve more realistic virtual-real fusion effects
Web Applications
Online Depth Map Generation
Process user-uploaded images directly in the browser and return depth maps
No server-side processing required
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