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alicevision/Meshroom

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12,562 stars·1,194 forks·QML·other·23 viewsalicevision.org↗

Meshroom

Meshroom is a node-based photogrammetry software designed to transform collections of two-dimensional images into three-dimensional models and scene geometry. It provides a visual interface for constructing and managing modular data pipelines, allowing users to automate complex computer vision tasks such as feature extraction, depth map estimation, and mesh generation.

The software distinguishes itself through a distributed computational framework that dispatches resource-intensive tasks across local hardware or remote render farms. By utilizing a directed acyclic graph execution model, it enables granular control over processing sequences, while intermediate result caching ensures that only affected segments of a pipeline are recomputed during iterative adjustments.

The platform supports a broad range of capabilities, including geospatial modeling through GPS integration, high-dynamic-range panorama generation, and the creation of Gaussian splat models. It also incorporates machine learning tools for depth estimation and language-based image segmentation, alongside mesh optimization features for refining geometry and texture mapping.

Interoperability is facilitated through data exchange protocols that connect reconstruction pipelines with external 3D modeling software. The system is built upon the AliceVision computer vision framework, providing a modular architecture that supports custom plugin development and hardware-accelerated processing.

Features

  • 3D Reconstruction Pipelines - Provides a comprehensive photogrammetry pipeline for converting sets of 2D photographs into accurate 3D digital models and scene geometry.
  • Reconstruction Tools - Transforms collections of two-dimensional images into three-dimensional models using an integrated photogrammetry and computer vision framework.
  • Camera Tracking - Performs precise camera tracking and scene alignment for digital production and visual effects.
  • Feature Extraction - Computes scale-invariant feature transforms on graphics hardware to enable high-speed image matching and camera tracking.
  • Nodal Workflow Designers - Enables users to construct complex, modular processing workflows through a visual nodal interface for managing data-intensive tasks.
  • Distributed Computing Frameworks - Dispatches resource-intensive reconstruction tasks across local hardware or remote render farms to optimize processing performance.
  • Gaussian Splatting - Creates 3D Gaussian splat models from multi-view image sets to enable high-quality rendering of new viewpoints.
  • Directed Acyclic Graph Execution Engines - Processes data through a sequence of interconnected nodes using a directed acyclic graph execution model.
  • Node-Based Architectures - Manages complex data transformations by allowing users to visually link modular processing units into custom reconstruction sequences.
  • Visual Pipeline Builders - Provides a visual nodal interface to construct modular data workflows, supporting reusable templates and deep customization of processing steps.
  • Depth Estimation - Predicts depth information from images using machine learning models to perform robust analysis of complex scenes.
  • Computer Vision Workflows - Orchestrates end-to-end computer vision tasks including feature extraction, depth map estimation, and mesh generation within a modular workflow.
  • GPU Accelerated Computer Vision - Offloads intensive image feature extraction and geometric reconstruction tasks to graphics hardware for high-speed performance.
  • Computer Vision - 3D reconstruction software based on photogrammetry.
  • Computer Vision and Image Processing - 3D reconstruction software based on photogrammetry.
  • Photogrammetry and Scanning - Free, open-source 3D photogrammetry software.
  • 3D Modeling and Animation - Framework for 3D reconstruction from photographs.
  • Fiducial Marker Detection - Identifies and tracks concentric circle markers in images to support robust camera tracking and scene alignment.
  • Node Result Caches - Uses node-based result caching to ensure only affected segments of a pipeline are recomputed during iterative adjustments.
  • Distributed Processing - Dispatches and manages heavy reconstruction tasks across local hardware or remote render farms to optimize execution speed.
  • Distributed Task Schedulers - Routes computational workloads to local or remote hardware farms by matching resource requirements to available capacity.
  • Georeferencing - Integrates real-world location data by mapping 3D reconstructions against GPS coordinates and global elevation models.
  • Farm Dispatchers - Dispatches processing jobs to external hardware farms by matching specific node requirements for CPU, RAM, and GPU resources.
  • Mesh Optimization - Refines 3D models by decimating geometry and applying new textures to improve performance and appearance.
  • Geospatial Terrain Visualization - Maps three-dimensional reconstructions against real-world geographic datasets and GPS coordinates to create accurate models of physical environments.
  • Modular Plugin Architectures - Separates core reconstruction logic from individual processing steps to allow for independent development and integration of new algorithms.
  • Nodal Reconstruction Editors - Provides a graphical nodal editor for constructing and managing reusable sequences of image-based reconstruction and geometry optimization steps.
  • Distributed Computing - Executes processing pipelines across local or remote hardware while managing node locking and resource monitoring for parallel tasks.
  • Panorama Generation - Merges bracketed images into high-dynamic-range panoramas while accounting for fisheye optics and camera metadata.
  • External Software Interoperability - Enables data exchange between reconstruction pipelines and external modeling tools to simplify production workflows.

Star history

Star history chart for alicevision/meshroomStar history chart for alicevision/meshroom

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does alicevision/meshroom do?

Meshroom is a node-based photogrammetry software designed to transform collections of two-dimensional images into three-dimensional models and scene geometry. It provides a visual interface for constructing and managing modular data pipelines, allowing users to automate complex computer vision tasks such as feature extraction, depth map estimation, and mesh generation.

What are the main features of alicevision/meshroom?

The main features of alicevision/meshroom are: 3D Reconstruction Pipelines, Reconstruction Tools, Camera Tracking, Feature Extraction, Nodal Workflow Designers, Distributed Computing Frameworks, Gaussian Splatting, Directed Acyclic Graph Execution Engines.

Which projects share features with alicevision/meshroom?

Projects with overlapping indexed features include: bytedance-seed/depth-anything-3 — Depth-Anything-3 is a collection of core model implementations for depth prediction, multi-view geometry estimation,… dask/dask — Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows… kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… open-mmlab/mmsegmentation — MMSegmentation is an open-source semantic segmentation toolbox built on PyTorch that provides a modular, configurable… graphdeco-inria/gaussian-splatting — Gaussian Splatting is a computational framework designed to transform sparse sets of two-dimensional photographs into…