Ml Depth Pro

Acest proiect este un model de estimare a adâncimii monoculare și un framework de computer vision conceput pentru a calcula distanța absolută și scara din imagini unice. Funcționează ca un estimator de adâncime metrică care generează hărți de adâncime de înaltă rezoluție fără a necesita metadate despre distanța focală specifice camerei.

Sistemul utilizează o arhitectură vision transformer pentru extragerea caracteristicilor și inferență zero-shot pentru a produce predicții de adâncime la scară metrică. Include componente specializate pentru rafinarea adâncimii la margini ascuțite pentru a menține detaliile de înaltă frecvență și a preveni neclaritatea la limitele obiectelor.

Repository-ul oferă, de asemenea, un framework de evaluare a hărților de adâncime. Acesta include utilitare pentru evaluarea limitelor de adâncime și metrici de acuratețe pentru a măsura precizia marginilor estimate față de datele ground truth.

Features

Monocular Depth Estimators - Acts as a monocular depth estimator that predicts metric depth from single images without camera metadata.
Computer Vision Models - Implements a neural network architecture designed for high-precision depth boundary analysis.
Metric Depth Estimators - Implements a model that outputs depth values in real-world units for absolute distance measurements.
Single-Image Metric Depth Mappers - Provides the capability to generate metric-scale depth maps from a single image input.
Depth Map Evaluation - Includes a framework to assess the precision of estimated depth boundaries against ground truth data.
Computer Vision - Provides a framework for analyzing image spatiality and structural boundaries for scene understanding.
Vision Transformer Encoders - Utilizes a vision transformer architecture to encode global context and local details.
Depth Accuracy Metrics - Provides utilities for calculating boundary metrics to measure the precision of estimated distance data.
Depth Map Evaluation Frameworks - Ships a framework of boundary metrics to measure depth map accuracy against ground truth.
Boundary Precision Metrics - Implements specialized boundary metrics to measure the precision of edges in estimated depth maps.
Edge Detail Refinements - Includes specialized components to maintain sharp object boundaries and prevent blurriness in depth maps.

Istoric stele

appleml-depth-pro

Name: apple/ml-depth-pro
Author: apple

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5,577 stele420 fork-uriPython2 vizualizări

Ml Depth Pro

Features

Monocular Depth Estimators - Acts as a monocular depth estimator that predicts metric depth from single images without camera metadata.
Computer Vision Models - Implements a neural network architecture designed for high-precision depth boundary analysis.
Metric Depth Estimators - Implements a model that outputs depth values in real-world units for absolute distance measurements.
Single-Image Metric Depth Mappers - Provides the capability to generate metric-scale depth maps from a single image input.
Depth Map Evaluation - Includes a framework to assess the precision of estimated depth boundaries against ground truth data.
Computer Vision - Provides a framework for analyzing image spatiality and structural boundaries for scene understanding.
Vision Transformer Encoders - Utilizes a vision transformer architecture to encode global context and local details.
Depth Accuracy Metrics - Provides utilities for calculating boundary metrics to measure the precision of estimated distance data.
Depth Map Evaluation Frameworks - Ships a framework of boundary metrics to measure depth map accuracy against ground truth.
Boundary Precision Metrics - Implements specialized boundary metrics to measure the precision of edges in estimated depth maps.
Edge Detail Refinements - Includes specialized components to maintain sharp object boundaries and prevent blurriness in depth maps.

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Întrebări frecvente

Ce face apple/ml-depth-pro?

Care sunt principalele funcționalități ale apple/ml-depth-pro?

Principalele funcționalități ale apple/ml-depth-pro sunt: Monocular Depth Estimators, Computer Vision Models, Metric Depth Estimators, Single-Image Metric Depth Mappers, Depth Map Evaluation, Computer Vision, Vision Transformer Encoders, Depth Accuracy Metrics.

Care sunt câteva alternative open-source pentru apple/ml-depth-pro?

Alternativele open-source pentru apple/ml-depth-pro includ: liheyoung/depth-anything — Depth-Anything is a monocular depth estimation foundation model that produces dense per-pixel depth maps from a single… pytorch/vision — This project is a comprehensive computer vision library for the PyTorch ecosystem, providing a standardized collection… depthanything/depth-anything-v2 — Depth-Anything-V2 is a computer vision foundation model designed for general-purpose spatial understanding and depth… nianticlabs/monodepth2 — This project is a computer vision system for monocular depth estimation and 3D point cloud generation. It provides a… pytorch/examples — This repository serves as a comprehensive collection of reference implementations for the PyTorch machine learning… tingsongyu/pytorch_tutorial — This project is a comprehensive collection of educational examples and reference implementations for building vision…

Ml Depth Pro

Features

Istoric stele

Ml Depth Pro

Features

Alternative open-source pentru Ml Depth Pro

LiheYoung/Depth-Anything

pytorch/vision

DepthAnything/Depth-Anything-V2

nianticlabs/monodepth2

Întrebări frecvente

Istoric stele

Alternative open-source pentru Ml Depth Pro

LiheYoung/Depth-Anything

pytorch/vision

DepthAnything/Depth-Anything-V2

nianticlabs/monodepth2

Întrebări frecvente