Search Results for "3d -engine -framework"
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Showing 51 open source projects for "3d -engine -framework"
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. ... -
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based modeling experiments. ... -
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plotly.py
The interactive graphing library for Python
...Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud. -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. ... -
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VGGT-Ω
[CVPR 2026 Oral] VGGT Omega
...VGGT-Omega is best suited for researchers and developers working on 3D reconstruction, visual geometry, and image-based scene understanding. -
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BlenderProc
Blender pipeline for photorealistic training image generation
...Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance, semantic segmentation, etc.) for each of those camera poses. Usually, you will run your script multiple times, each time producing a new scene and rendering e.g. 5-20 images from it. With a little more experience, it is also possible to change scenes during a single script call, read here how this is done. ... -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). Matplotlib is the brainchild of John Hunter (1968-2012), who, along with its many contributors, have put an immeasurable amount of time and effort into producing a piece of software utilized by thousands of scientists worldwide. ... -
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ModernGL
Modern OpenGL binding for Python
ModernGL is a Python wrapper over OpenGL, designed to simplify the creation of high-performance, modern graphics applications. It provides an intuitive API for rendering 2D and 3D graphics, making it accessible to both beginners and experienced developers. ModernGL is suitable for applications such as games, simulations, and data visualizations. -
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DeepSeed
Deep learning optimization library making distributed training easy
...DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. ... -
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Copulas
A library to model multivariate data using copulas
...Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D histograms, 2D scatterplots and 3D scatterplots. Access & manipulate learned parameters. With complete access to the internals of the model, set or tune parameters to your choosing. -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. ... -
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PyG
Graph Neural Network Library for PyTorch
...In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. ... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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SmartNode
Visual simulation platform for space-based data backhaul scenarios
smartNode is a visual simulation platform for space-based intelligent relay and satellite data-return scenarios. It models the relationship between satellites, ground stations, relay links, and content-driven task scheduling. The project includes a Python backend and a browser-based frontend, making it suitable for local simulation, teaching, and secondary development. Users can view a three-dimensional space situation, submit data return tasks, and monitor resource states in real time. The... -
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dj-stripe
dj-stripe automatically syncs your Stripe Data to your local database
Dj-stripe is an extensible wrapper around the Stripe API that continuously syncs most of the Stripe Data to your local database as pre-implemented Django Models, out of the box! This allows you to use the Django ORM, in your code, to work with the data making it easier and faster! For example, if you need to interact with a customer subscription, you can use dj-stripe’s Subscription Model, in your code, to get the subscription data for that customer as well as the related models’ data too... -
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3D Box rotation
Simple example of draw and rotate 3D box
Simple source .java file; .bat for fast re-compile and run; and pre-compiled .jar Java program with example from scratch writed in Notepad++ without Eclipse, etc., How to draw and rotate 3D box most simple way. Rotation speed regulated in simple Loop with 10 ms sleep. Use Java version 8 (OpenJDK 8, OracleJDK 8, OracleJRE 8, ..). Higher versions have an anti-aliasing error in the BufferedImage ( Windows 10 ). Python version with tkinter and math imports. Including calculated faces, moving lights and shadows only with CPU. -
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PoJamas aims to provide a Python and tools for loading, processing, and producing .cr2, pz3 (crz, pzz) files compatible with the SmithMicro (e-frontier) Poser character animation application. PoJamas is composed of: - Python library - Python Wavefront (.obj) 3D viewer based on GLFW - LibreOffice/Python Application (to ease the library and the viewer usage) As of 2020, the project is ported in Python3 As of 2021 this project proposes a 3D viewer for Wavefront files (pypos3dv) PyPosPosLO v0.15 (and above) provides the means to easily create Poser Mechanical Character. Results can be seen here: https://sharecg.com/v/94509/view/11/Poser/Hawker-Tempest-Character-v2
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geometry3d
A Python library for geometric objects in 3 dimentions
Implemented classes of 3d objects: * Vector * Point * Line * Plane * LineSegment Yet incompletely implemented classes: * Triangle * Disk (closed circle) * Union (a collection of 3d objects) Each object has methods for finding its sizes, containing box or containing sphere. It finds intersection and distance or closest to another object part of itself. -
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Glumpy
Python+Numpy+OpenGL, scalable and beautiful scientific visualization
Glumpy is a Python library that simplifies the development of high-performance, interactive OpenGL visualizations. It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and... -
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hloc
Visual localization made easy with hloc
...We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using SfM. Just download the datasets and you're reading to go! The notebook pipeline_InLoc.ipynb shows the steps for localizing with InLoc. It's much simpler since a 3D SfM model is not needed. We show in pipeline_SfM.ipynb how to run 3D reconstruction for an unordered set of images. This generates reference poses, and a nice sparse 3D model suitable for localization with the same pipeline as Aachen. -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
...DockStream can also parallelize docking across CPU cores, increasing throughput. DockStream is integrated with the de novo design platform, REINVENT, allowing one to incorporate docking into the generative process, thus providing the agent with 3D structural information. -
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OpenFrames
Real-time interactive 3D graphics API for scientific simulations
...Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently used by three NASA programs: Copernicus (NASA JSC), the General Mission Analysis Tool (GMAT, NASA GSFC), and a Virtual Reality exploration tool (NASA GSFC). -
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Makani
Makani was developed a commercial-scale airborne wind turbine
Makani was an ambitious Google X project that sought to harness wind energy using airborne wind turbines — autonomous kites capable of generating power while flying in crosswind patterns. This open-source repository contains the complete software stack that powered Makani’s research and flight systems, including the flight simulator, autopilot controller, avionics firmware, visualization tools, and ground control software. The software enables simulation, control, and analysis of the Makani...
