Was sind die Hauptfunktionen von apple/ml-depth-pro?

Die Hauptfunktionen von apple/ml-depth-pro sind: 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.

Welche Open-Source-Alternativen gibt es zu apple/ml-depth-pro?

Open-Source-Alternativen zu apple/ml-depth-pro sind unter anderem: 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…

appleml-depth-pro

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

View on GitHub

5,577 Stars420 ForksPython2 Aufrufe

Ml Depth Pro

Dieses Projekt ist ein monokulares Tiefenschätzungsmodell und ein Computer-Vision-Framework, das darauf ausgelegt ist, absolute Distanz und Skalierung aus einzelnen Bildern zu berechnen. Es fungiert als metrischer Tiefenschätzer, der hochauflösende Tiefenkarten generiert, ohne kameraspezifische Brennweiten-Metadaten zu benötigen.

Das System nutzt eine Vision-Transformer-Architektur für die Merkmalsextraktion und Zero-Shot-Inferenz, um Tiefenvorhersagen im metrischen Maßstab zu erstellen. Es beinhaltet spezialisierte Komponenten für die Verfeinerung scharfer Tiefengrenzen, um hochfrequente Kantendetails zu erhalten und Unschärfe an Objektgrenzen zu verhindern.

Das Repository bietet zudem ein Framework zur Bewertung von Tiefenkarten. Dies beinhaltet Utilities für die Bewertung von Tiefengrenzen und Genauigkeitsmetriken, um die Präzision geschätzter Kanten gegen Ground-Truth-Daten zu messen.

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.

Star-Verlauf

appleml-depth-pro

View on GitHub

5,577 Stars420 ForksPython2 Aufrufe

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.

Open-Source-Alternativen zu Ml Depth Pro

Ähnliche Open-Source-Projekte, sortiert nach der Anzahl der gemeinsamen Funktionen mit Ml Depth Pro.

liheyoung/depth-anything
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nianticlabs/monodepth2
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This project is a computer vision system for monocular depth estimation and 3D point cloud generation. It provides a supervised depth learning framework and a depth predictor capable of estimating spatial distance and disparity from single 2D images using pretrained neural networks. The system includes tools to transform 2D depth images into 3D point clouds via pixel coordinate backprojection and converts 3D point cloud data into 2D depth maps. It utilizes a training pipeline that supports model fine-tuning and hyperparameter optimization. The library covers broader capabilities in spatial a
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Alle 30 Alternativen zu Ml Depth Pro anzeigen

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Was macht apple/ml-depth-pro?

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Open-Source-Alternativen zu Ml Depth Pro

Ähnliche Open-Source-Projekte, sortiert nach der Anzahl der gemeinsamen Funktionen mit Ml Depth Pro.

liheyoung/depth-anything
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8,124Auf GitHub ansehen
Depth-Anything is a monocular depth estimation foundation model that produces dense per-pixel depth maps from a single RGB image. It is built on a DINOv2 Vision Transformer encoder backbone and trained on 62 million unlabeled images using a teacher-student pseudo-labeling framework, enabling robust generalization across diverse scenes without task-specific training. The model outputs both relative depth maps, which capture the ordering of scene points, and metric depth maps with real-world units after fine-tuning on datasets like NYUv2 or KITTI. The project distinguishes itself through its ab
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pytorch/vision
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This project is a comprehensive computer vision library for the PyTorch ecosystem, providing a standardized collection of neural network architectures, datasets, and high-performance transformation utilities. It serves as a foundational framework for building, training, and deploying deep learning models, offering a centralized model registry that allows developers to instantiate architectures with pre-trained weights for tasks such as image classification, object detection, and semantic segmentation. The library distinguishes itself through its modular approach to data and compute management
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depthanything/depth-anything-v2
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nianticlabs/monodepth2
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This project is a computer vision system for monocular depth estimation and 3D point cloud generation. It provides a supervised depth learning framework and a depth predictor capable of estimating spatial distance and disparity from single 2D images using pretrained neural networks. The system includes tools to transform 2D depth images into 3D point clouds via pixel coordinate backprojection and converts 3D point cloud data into 2D depth maps. It utilizes a training pipeline that supports model fine-tuning and hyperparameter optimization. The library covers broader capabilities in spatial a
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Alle 30 Alternativen zu Ml Depth Pro anzeigen

Ml Depth Pro

Features

Star-Verlauf

Ml Depth Pro

Features

Open-Source-Alternativen zu Ml Depth Pro

LiheYoung/Depth-Anything

pytorch/vision

DepthAnything/Depth-Anything-V2

nianticlabs/monodepth2

Häufig gestellte Fragen

Star-Verlauf

Open-Source-Alternativen zu Ml Depth Pro

LiheYoung/Depth-Anything

pytorch/vision

DepthAnything/Depth-Anything-V2

nianticlabs/monodepth2

Häufig gestellte Fragen