Search Results for "3d model viewer"
Sort By:
Showing 56 open source projects for "3d model viewer"
View related business solutions-
Earn up to 16% annual interest with Nexo.Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
-
1
glslViewer
Console-based GLSL Sandbox for 2D/3D shaders shaders
GlslViewer is a flexible console-based OpenGL Sandbox to display 2D/3D GLSL shaders without the need of a UI. You can definitely make your own UI or wrapper using the Python Module (include) or any other tool that communicates back/forth with the GPS viewer through the standard POSIX console In/Out or OSC. Default vert/frag shaders for 2D shader and 3D material shaders with PBR lighting model. Hot reload of files on changes. -
2
Netron
Visualizer for neural network, deep learning, machine learning models
...There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser. -
3
CadQuery
A python parametric CAD scripting framework based on OCCT
...Provide a non-proprietary, plain text model format that can be edited and executed with only a web browser. The scripts use a standard programming language, Python, and thus can benefit from the associated infrastructure. This includes many standard libraries and IDEs. CadQuery's CAD kernel Open CASCADE Technology (OCCT) is much more powerful than the CGAL used by OpenSCAD. -
4
Google Cardboard XR Plugin for Unity
Google Cardboard XR plugin for Unity
This SDK provides everything you need to create your own Virtual Reality (VR) experiences for Google Cardboard in Unity 2019.4.25f1 or later. It supports essential VR features, such as motion tracking, stereoscopic rendering, and user interaction via the viewer button. With these capabilities, you can build entirely new VR experiences, or enhance existing apps with VR capabilities. You can use the Cardboard SDK to turn a smartphone into a VR platform. A smartphone can display 3D scenes with stereoscopic rendering, track and react to head movements, and interact with apps by detecting when the user presses the viewer button. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
KiCad
This is an active mirror of the KiCad development branch
KiCad's PCB Editor is approachable enough to make your first PCB design easy, and powerful enough for complex modern designs. A powerful interactive router and improved visualization and selection tools make layout tasks easier than ever. This is an active mirror of the KiCad development branch, which is hosted at GitLab (updated every time something is pushed). -
6
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. -
7
Chili3D
A browser-based 3D CAD application for online model design
Chili3D is an open-source, browser-based 3D CAD application that enables users to design, edit, and visualize complex 3D models directly within a web environment without requiring local installation. It is built using TypeScript and leverages WebAssembly to compile the OpenCascade geometric modeling kernel, allowing it to achieve near-native performance inside the browser. The application integrates with modern rendering libraries to provide real-time visualization, interactive modeling, and... -
8
Draper
Decorators/view-models for Rails applications
Draper adds an object-oriented layer of presentation logic to your Rails application. Without Draper, this functionality might have been tangled up in procedural helpers or adding bulk to your models. With Draper decorators, you can wrap your models with presentation-related logic to organize and test this layer of your app much more effectively. Imagine your application has an Article model. With Draper, you'd create a corresponding ArticleDecorator. The decorator wraps the model, and deals... -
9
Perfetto
Production-grade client-side tracing, profiling, and analysis
Perfetto is a production-grade tracing platform for Android, Linux, and Chrome that captures extremely detailed information about what a system is doing over time. It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
10
Filament
Real-time physically based rendering engine for Android, iOS, and more
...Filament is a physically based rendering (PBR) engine for Android. The goal of Filament is to offer a set of tools and APIs for Android developers that will enable them to create high quality 2D and 3D rendering with ease. For both artists and developers, our system will rely on as few parameters as possible to reduce trial and error and allow users to quickly master the material model. A physically based approach must not preclude non-realistic rendering. User interfaces for instance will need unlit materials. Our primary goal is to design and implement a rendering system able to perform efficiently on mobile platforms. -
11
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). -
12
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... -
13
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
-
14
Kisekae UltraKiss
Kisekae UltraKiss is a full featured integrated development environmen
UltraKiss is a computer program that implements the Kisekae Set system, KiSS, a Japanese graphics system originally developed to facilitate costume changes on virtual dolls. UltraKiss was developed to help artists build their KiSS sets. It is a full featured viewer for all KiSS dolls, games, and visual applications. It is also a complete graphical development environment for creating KiSS applications. It fully implements the FKiSS event driven programming language up to and including... -
15
towhee
Framework that is dedicated to making neural data processing
...You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. ... -
16
Sceneform Maintained SDK for Android
Sceneform Maintained is an ARCore Android SDK with Google Filament
Sceneform Maintained is an ARCore Android SDK with Google Filament as 3D engine. This is the continuation of the Archived Sceneform. Android Augmented Reality library: AR Model Viewer, Augmented Images, Augmented Faces, Video, Depth, Cloud Anchors, Instant Placement, Light Estimation and much more in Kotlin and Java. -
17
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. -
18
GFPGAN
GFPGAN aims at developing Practical Algorithms
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing... -
19
Blend_My_NFTs
Easily generate thousands of 3D models, images, and animation NFTs
Blend_My_NFTs is an open-source, free-to-use Blender add-on that enables you to easily generate thousands of 3D Models, Animations, and Images. This add-on's primary purpose is to aid in the creation of large generative 3D NFT collections. It is the first and easiest 3D NFT generator. Blend_My_NFTs was initially developed to create Cozy Place, an NFT collection by This Cozy Studio Inc. Blend_My_NFTs works with Blender 3.2.2 on Windows 10 or macOS Big Sur 11.6. ... -
20
LaMa
LaMa - A Localization and Mapping library
LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our localization and SLAM solutions is a Raspberry Pi 3 Model B+. ... -
21
GroIMP
Growth-grammar related Interactive Modelling Platform
Important: Groimp migrates to Gitlab. You can find the latest code at "https://gitlab.com/grogra/groimp/". The version on Sourceforge will not be updated anymore. The modelling platform GroIMP is designed as an integrated platform which incorporates modelling, visualisation and interaction. It exhibits several features which makes itself suitable for the field of biological or ALife modelling: The “modelling backbone” consists in the language XL. It is fully integrated, e.g., the... -
22
Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! -
23
Quan is designed to model physical quantities in C++ programs. Advantages include automated dimensional analysis checking, automatic unit conversions, self documentation of code.
-
24
I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. ... -
25
TenorSpace.js
Neural network 3D visualization framework
TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information.
