Search Results for "3d model slicer"
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Showing 185 open source projects for "3d model slicer"
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Blockbench
Blockbench - A low poly 3D model editor
Blockbench is a free, modern model editor for low-poly and boxy models with pixel art textures. Models can be exported into standardized formats, to be shared, rendered, 3D-printed, or used in game engines. There are also multiple dedicated formats for Minecraft Java and Bedrock Edition with format-specific features. Blockbench features a modern and intuitive UI, plugin support and innovative features. It is the industry standard for creating custom 3D models for the Minecraft Marketplace... -
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Dust3D
Dust3D is a cross-platform open-source 3D modeling software
Dust3D is brand new 3D modeling software. It lets you create watertight 3D models in seconds. Use it to speed up character modeling for games, 3D printing, and so on. Auto UV unwrapping, auto rigging with PBR Material support, pose and motion authoring all in one. 3D Modeling in a blink, try it now! Dust3D is a cross-platform open-source modeling software. It helps you create a 3D watertight model in seconds. Use it to speed up your character modeling in game making, 3D printing, and so on. Yes... -
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MeshLab
The open source mesh processing system
MeshLab is an open-source, portable, and extensible system for the processing and editing of unstructured large 3D triangular meshes. It is aimed to help the processing of the typical not-so-small unstructured models arising in 3D scanning, providing a set of tools for editing, cleaning, healing, inspecting, rendering and converting this kind of meshes. MeshLab is mostly based on the open source C++ mesh processing library VCGlib developed at the Visual Computing Lab of ISTI - CNR. VCG can... -
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FreeCAD
A free and open source multiplatform 3D parametric modeler
FreeCAD is an open-source parametric 3D modeler made primarily to design real-life objects of any size. Parametric modeling allows you to easily modify your design by going back into your model history and changing its parameters. FreeCAD allows you to sketch geometry constrained 2D shapes and use them as a base to build other objects. It contains many components to adjust dimensions or extract design details from 3D models to create high quality production ready drawings. FreeCAD... -
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OpenSCAD
The programmer's solid 3D CAD modeller
...-animated movies. OpenSCAD is not an interactive modeller. Instead it is something like a 3D-compiler that reads in a script file that describes the object and renders the 3D model from this script file. This gives you (the designer) full control over the modelling process and enables you to easily change any step in the modelling process or make designs that are defined by configurable parameters. -
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CadQuery
A python parametric CAD scripting framework based on OCCT
CadQuery is an intuitive, easy-to-use Python library for building parametric 3D CAD models. It has several goals. Build models with scripts that are as close as possible to how you’d describe the object to a human, using a standard, already established programming language. Create parametric models that can be very easily customized by end users. Output high-quality CAD formats like STEP and AMF in addition to traditional STL. Provide a non-proprietary, plain text model format that can... -
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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. One default light and one default camera. Interactive commands thought... -
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Stable-Dreamfusion
Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion
A pytorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. This project is a work-in-progress and contains lots of differences from the paper. The current generation quality cannot match the results from the original paper, and many prompts still fail badly! Since the Imagen model is not publicly available, we use Stable Diffusion to replace it (implementation from diffusers). Different from Imagen, Stable-Diffusion is a latent diffusion... -
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Filament
Real-time physically based rendering engine for Android, iOS, and more
... 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. -
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OpenSCAD Graph Editor
OpenSCAD Graph Editor
OpenSCAD Graph Editor is a graphical user interface for OpenSCAD that allows you to create 3D models by connecting nodes in a graph. The editor will automatically generate OpenSCAD code for you. It integrates with the OpenSCAD program so you can preview your models in real-time while you are editing the graph. Please check the manual to find out how to install and use the program. -
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Make-A-Video - Pytorch (wip)
Implementation of Make-A-Video, new SOTA text to video generator
Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch. They combine pseudo-3d convolutions (axial convolutions) and temporal attention and show much better temporal fusion. The pseudo-3d convolutions isn't a new concept. It has been explored before in other contexts, say for protein contact prediction as "dimensional hybrid residual networks". The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning... -
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Video Diffusion - Pytorch
Implementation of Video Diffusion Models
Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. It uses a special space-time factored U-net, extending generation from 2D images to 3D videos. 14k for difficult moving mnist (converging much faster and better than NUWA) - wip. Any new developments for text-to-video synthesis will be centralized at Imagen-pytorch... -
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PyG
Graph Neural Network Library for PyTorch
... 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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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. 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... -
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Aphantasia
CLIP + FFT/DWT/RGB = text to image/video
This is a collection of text-to-image tools, evolved from the artwork of the same name. Based on CLIP model and Lucent library, with FFT/DWT/RGB parameterizes (no-GAN generation). Illustrip (text-to-video with motion and depth) is added. DWT (wavelets) parameterization is added. Check also colabs below, with VQGAN and SIREN+FFM generators. Tested on Python 3.7 with PyTorch 1.7.1 or 1.8. Generating massive detailed textures, a la deepdream, fullHD/4K resolutions and above, various CLIP models... -
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eos
A lightweight 3D Morphable Face Model library in modern C++
eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14. MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like draw_sample(). Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-box. -
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Copulas
A library to model multivariate data using copulas
... 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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hloc
Visual localization made easy with hloc
.... 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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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... -
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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. -
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Segments.ai
Segments.ai Python SDK
Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML... -
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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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DeepSpeed
Deep learning optimization library: makes distributed training easy
... compression for an unparalleled inference latency and model size reduction with low costs DeepSpeed offers a confluence of system innovations, that has made large scale DL training effective, and efficient, greatly improved ease of use, and redefined the DL training landscape in terms of scale that is possible. These innovations such as ZeRO, 3D-Parallelism, DeepSpeed-MoE, ZeRO-Infinity, etc. fall under the training pillar. -
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Diffusers
State-of-the-art diffusion models for image and audio generation
Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions. State-of-the-art diffusion pipelines that can be run in inference with just a few... -
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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. Linux is supported, however we...