mujoco_menagerie is a curated library of physical robot specifications and XML model definitions designed for standardized dynamics and contact simulation. It provides a collection of high-quality robot model files for humanoids, quadrupeds, and manipulators, alongside detailed kinematic and inertial parameters used to reproduce real-world robot behavior in virtual environments. The project serves as a repository of robotics simulation assets and MJCF model definitions optimized for accuracy. It includes standardized model libraries specifically for bipedal, quadrupedal, and humanoid hardware
TextRecognitionDataGenerator is a system for creating synthetic text images and character masks to train and test optical character recognition models. It functions as a dataset tool that generates artificial images by combining dictionary words with specific fonts and backgrounds to produce training sets for machine learning. The project includes a handwriting simulation engine that uses machine learning models to produce synthetic handwritten text. It also features a document degradation simulator that applies skew, blur, and distortion to images to mimic the visual quality of scanned physi
gofakeit is a Go library for creating realistic synthetic datasets and populating Go structs with mock information. It functions as a deterministic data generator, allowing for seedable random number generation to ensure reproducible datasets for software testing. The project distinguishes itself by providing a mock data API server that exposes generation functions as HTTP endpoints and a synthetic dataset exporter for producing files in CSV, JSON, and XML formats. It also includes a command-line interface for generating mock data directly from the terminal. The library covers a wide array o
Armortools is a 3D PBR texture painting suite and mesh texture workflow tool. It provides a system for painting physically based rendering materials directly onto 3D meshes using a combination of layer and mask support, a GPU-accelerated texture baker for extracting geometry data from high-polygon models, and a node-based material editor for creating procedural textures. The software features integrated neural network tools for AI texture authoring, allowing the generation of PBR maps from text prompts, image-based material extraction, and texture upscaling via local nodes. It also implements
Infinigen is a procedural 3D scene generation framework that creates photorealistic indoor and outdoor environments for computer vision training data. It combines constraint-based object placement, GPU geometry shaders, and ground-truth rendering passes to produce scenes with depth, normals, and segmentation masks alongside final images.
Las características principales de princeton-vl/infinigen son: Procedural Generators, Procedural Scene Generators, Synthetic Training Data Generators, Multi-Channel Render Passes, Embedded Physics Solvers, Random Number Generator Seeding, Rule-Based Layout Systems, Procedural Geometry Shaders.
Las alternativas de código abierto para princeton-vl/infinigen incluyen: google-deepmind/mujoco_menagerie — mujoco_menagerie is a curated library of physical robot specifications and XML model definitions designed for… belval/textrecognitiondatagenerator — TextRecognitionDataGenerator is a system for creating synthetic text images and character masks to train and test… carson-katri/dream-textures — Dream Textures is a Stable Diffusion integration for Blender that provides tools for text-to-image generation, depth… armory3d/armortools — Armortools is a 3D PBR texture painting suite and mesh texture workflow tool. It provides a system for painting… brianvoe/gofakeit — gofakeit is a Go library for creating realistic synthetic datasets and populating Go structs with mock information. It… chancejs/chancejs — Chance is a JavaScript library for generating random data, designed to produce realistic test data for automated tests…