Search Results for "convert point cloud"
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Showing 18 open source projects for "convert point cloud"
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. -
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CompressO
Convert any video/image into a tiny size. 100% free & open-source
compressO is a cross-platform, open-source multimedia compression application designed to reduce the size of videos and images while preserving visual quality. Built using modern frameworks such as Rust and Tauri, it runs locally on the user’s machine, ensuring fast performance and complete privacy without requiring cloud processing. The application supports a variety of media formats and provides controls for adjusting compression levels, resolution, and output quality. In addition to... -
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go2rtc
Ultimate camera streaming application
go2rtc is a lightweight, zero-dependency streaming server designed to unify and convert video streams across a wide range of protocols and devices, particularly in smart home and surveillance environments. Written in Go, it provides real-time streaming capabilities with extremely low latency by supporting protocols such as RTSP, WebRTC, RTMP, HTTP, and HomeKit, while also enabling seamless transcoding using FFmpeg when needed. -
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Speakr
Speakr is a personal, self-hosted web application
...The project is built with extensibility in mind, enabling developers to add custom voices, integrate additional languages, and tailor the backend for different hardware or cloud environments. It also supports saving generated audio as downloadable files so users can reuse the speech outputs in other projects, presentations, or media content. -
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TerraCognita
Reads from existing public and private cloud providers
Imports your current Cloud infrastructure to an Infrastructure As Code Terraform configuration (HCL) or/and to a Terraform State. At Cycloid, Infrastructure As Code is in the company's DNA since the beginning. To help our new customers adopt this best practice, we decided to build Terracognita to convert an existing infrastructure on Cloud Infrastructure into Terraform code in an automated way, relying on Terraform providers built by the community. -
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pyntcloud
pyntcloud is a Python library for working with 3D point clouds
This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. ... -
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generativeart
Create Generative Art with R
generativeart is an R package for creating algorithmic art by computing the positions of many thousands of points according to user-defined mathematical formulas with randomized parameters. Each render uses a seed to introduce controlled randomness, so every image is unique while remaining reproducible when the same seed and formula are reused. The package logs the seed, formula, and file name to a CSV, which makes it easy to catalog outputs, re-generate favorites, and track experiments. A... -
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AAXtoMP3
Convert Audible's .aax filetype to MP3, FLAC, M4A, or OPUS
AAXtoMP3 is a lightweight command-line tool that converts Audible audiobook files in AAX format into standard audio formats such as MP3 and M4A. It focuses on removing DRM restrictions locally, allowing users to retain access to their purchased audiobooks across devices. The tool uses FFmpeg for decoding and encoding, ensuring compatibility with a wide range of playback systems. It preserves chapter markers and metadata during conversion, maintaining the structure of the original audiobook.... -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists... -
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videotranscode.space
A video transcoder and converter built using Web Assembly
videotranscode.space is a web-based platform designed to simplify video transcoding through a user-friendly interface powered by backend FFmpeg processing. It allows users to upload media files and convert them into different formats or resolutions directly from the browser. The platform emphasizes accessibility by removing the need for local installations or command-line usage. It supports scalable processing, making it suitable for handling multiple conversion jobs in cloud environments. The system is designed with modern web technologies to provide fast and responsive interactions. ... -
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Point Cloud Skinner for Blender
Python script (addon) for Blender to skin point cloud (verts to face).
...Features: This script, Point Cloud Skinner can skin a cloud of vertices, which means to create a 3D surfaced mesh out of just a cloud of vertices that has no faces. It can skin any shapes of point clouds, such as a surveyed geography point cloud that represents a landform somewhere, a fluid volumetric point cloud obtained by numerical fluid simulation, or anything you like. -
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UML Reverse Mapper
Automatically generate class diagram from code
UML Reverse Mapper is a utility that helps convert existing code structures into UML-like representations so developers can visualize and reason about their systems. It is aimed at teams that inherit codebases or work on legacy projects and need a fast way to understand classes, relationships, and dependencies. Instead of drawing UML by hand, you point the tool at the code and let it generate artifacts that resemble standard UML diagrams. -
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Manifold mesh processing
Mesh and point cloud processing tools
A suite of tools for processing and analyzing meshes and point clouds. 1) Ensuring that meshes are manifold, ie, "nice" 2) Simple smoothing/noise reduction 3) Bare-bones point cloud to mesh and robust normals for point clouds 4) Mesh simplification 5) Curvature calculation on meshes 6) Local shape descriptors on meshes -
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Point Cloud Library
Standalone, large scale, open project for 3D point cloud processing.
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. We are financially supported by Open Perception, Willow Garage, NVIDIA, Google, Toyota, Trimble, Urban Robotics, Honda Research Institute, Sandia, Dinast, Optronic, Ocular Robotics, Velodyne, Fotonic, Leica Geosystems, and MKE. -
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ZPR is a program that produces orthophotos. The method used is to give colors to point-cloud (photo obtained by a digital camera, cloud obtained by a laser scanner) and to project the point-cloud to a requested plane. With this method, the projection pla
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Open source point cloud viewer forked from Radiohead House of Cards Project, based on the Processing Programming Language.
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The converter will convert INTERLIS 2 point symbols to symbols in the file format FSM. The first release will just be able to convert INTERLIS / XML to INTERLIS / XML. Further versions will convert INTERLIS / XML to FSM and the way back.
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PhotoCloud is a tool to browse and a navigate for datasets composed of (a) a collection of registered images and (b) a 3D model over which images are aligned. The 3D model can be a point-cloud, triangle mesh. PhotoCloud is based on a client/server architecture and it is scalable: very large dataset (both in terms of (a) and (b) can be handled.
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