Search Results for "objects detection"
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35 projects for "objects detection" with 1 filter applied:
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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Grounded-Segment-Anything
Marrying Grounding DINO with Segment Anything & Stable Diffusion
Grounded-Segment-Anything is a research-oriented project that combines powerful open-set object detection with pixel-level segmentation and subsequent creative workflows, effectively enabling detection, segmentation, and high-level vision tasks guided by free-form text prompts. The core idea behind the project is to pair Grounding DINO — a zero-shot object detector that can locate objects described by natural language — with Segment Anything Model (SAM), which can produce detailed masks for objects once they are localized. ... -
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RF-DETR
RF-DETR is a real-time object detection and segmentation
RF-DETR is an open-source computer vision framework that implements a real-time object detection and instance segmentation model based on transformer architectures. Developed by Roboflow, the project builds upon modern vision transformer backbones such as DINOv2 to achieve strong accuracy while maintaining efficient inference speeds suitable for real-time applications. The model is designed to detect objects and segment them within images or video streams using a unified detection pipeline. ... -
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Frigate NVR
NVR with realtime local object detection for IP cameras
Frigate is a local network video recorder designed for real-time object detection on IP camera streams using machine learning. It runs entirely on local hardware and integrates closely with Home Assistant to provide smart surveillance without relying on cloud processing. The system uses OpenCV and TensorFlow to analyze video feeds and detect objects such as people, vehicles, and animals in real time. Frigate is optimized for efficiency and supports hardware acceleration across a wide range of devices, including GPUs and specialized inference hardware. ... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. -
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BoxMOT
Pluggable SOTA multi-object tracking modules for segmentation
BoxMOT is an open-source framework designed to provide modular implementations of state-of-the-art multi-object tracking algorithms for computer vision applications. The project focuses on the tracking-by-detection paradigm, where objects detected by vision models are continuously tracked across frames in a video sequence. It provides a pluggable architecture that allows developers to combine different object detectors with multiple tracking algorithms without modifying the core codebase. The framework supports integration with detection, segmentation, and pose estimation models that produce bounding box outputs. ... -
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trackers
Multi-object tracking algorithms
trackers is a plug-and-play multi-object tracking library designed to work with virtually any object detection model, enabling developers to follow objects across video frames with minimal setup. The library provides clean, modular implementations of leading tracking algorithms and can be used either from the command line or embedded directly into Python pipelines. It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that include labels and trajectories. ... -
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future
R package: future: Unified Parallel and Distributed Processing in R
...This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. It handles automatic exporting of needed global variables/functions, managing of packages, RNG, etc. Automatic detection and export of global objects and functions needed by future expressions, so the user doesn’t need to manage that manually. Ability to control how futures are resolved. -
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Kint
Kint - Advanced PHP dumper
Kint is a PHP debugging tool that provides developers with an intuitive and highly informative way to inspect variables and data structures. It replaces standard debugging methods like var_dump() and print_r() with a more readable and structured output, highlighting key details and nesting. Kint is designed to simplify debugging by automatically detecting variable types and presenting them in a clean, interactive format. -
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.
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InternGPT
Open source demo platform where you can easily showcase your AI models
...Unlike traditional chat systems that rely solely on text prompts, InternGPT allows users to interact with visual content using both language and nonverbal signals such as pointing or highlighting objects within images. The framework connects multiple specialized AI models that perform tasks such as object detection, segmentation, captioning, and visual editing while coordinating them through a central conversational interface. This architecture enables the system to plan actions, execute visual operations, and return results in a coherent dialogue with the user. -
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Matter.js
A 2D rigid body physics engine for the web
Matter.js is a flexible 2D rigid body physics engine written in JavaScript, designed for use in web applications to simulate real-world physical interactions within the browser. It offers a comprehensive set of physics features like gravity, collisions, restitution (bounces), friction, sleeping bodies, and constraint systems that enable developers to build interacting objects with realistic motion. This engine can power everything from dynamic interactive animations and educational... -
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Isometric City
IsoCity: City building simulation game
...It uses optimized rendering techniques to draw tiles, buildings, roads, and terrain in isometric perspective, giving depth and dimension without 3D complexity, and includes a set of modular components so custom art or tile sets can be slotted in effortlessly. Users can pan and zoom smoothly across the scene, dynamically placing or editing objects, and the engine supports layered terrain, collision detection, and grid snapping to keep placements accurate and visually coherent. Although often used for game prototypes, the project’s flexible architecture also fits use cases like simulation dashboards, planning tools, or interactive data visualizations where spatial layout matters. -
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LLM Vision
Visual intelligence for your home.
LLM Vision is an open-source integration for Home Assistant that adds multimodal large language model capabilities to smart home environments. The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process... -
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libsombrero
Astronomical object/structure detection from 1D and 2D data sets.
Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library. -
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GLOBE_3D
A real-time 3D Engine written in Ada
GLOBE_3D: GL Object Based Engine for 3D. GLOBE_3D is a free, open-source, real-time 3D Engine written in Ada, based on OpenGL. Up-to-date GL bindings - portal rendering - binary space partition - object I/O - tools for importing - and more... More information on... http://globe3d.sf.net Alire crate: https://alire.ada.dev/crates/globe_3d Mirror: https://github.com/zertovitch/globe-3d/ -
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Castle Game Engine
Game engine supporting many 3D/2D formats and graphic effects
...Rendering and processing of game assets in glTF, X3D, VRML, Collada, Spine and other formats. Many graphic effects including shadows, shaders, mirrors, screen effects. Animation, collision detection, 3D sound. Extensible system of 3D objects, with out-of-the-box levels, items, intelligent creatures and more. Desktop, mobile, web plugin. Also home of view3dscene - our full-featured VRML/X3D browser. -
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YoloV3 Implemented in TensorFlow 2.0
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 is built using TensorFlow 2.0. The project provides a modern deep learning implementation of the popular YOLOv3 algorithm, which is widely used for real-time object detection in images and video streams. YOLOv3 works by dividing an image into grid regions and predicting bounding boxes and class probabilities simultaneously, allowing objects to be detected quickly and efficiently. The repository includes training scripts, inference tools, and configuration files that make it possible to train custom object detection models on user-defined datasets. ... -
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. ... -
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VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. -
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LUMINOTH
Deep Learning toolkit for Computer Vision
LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. Luminoth includes support for popular object detection architectures such as Faster R-CNN and SSD, enabling developers to train models on datasets like COCO and Pascal VOC. ... -
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FreeSOLID is a library for collision detection of three-dimensional objects undergoing rigid motion and deformation. FreeSOLID is designed to be used in interactive 3D graphics applications.
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Voxel CAD. Open source voxel editing and analyzing software. Edit and create multi-material voxel objects. Simulate the dynamics in a quantitative physics sandbox to test engineering designs or make moving creatures. www.voxcad.com for videos.
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A free, industrial quality library for simulating articulated rigid body dynamics - for example ground vehicles, legged creatures, and moving objects in VR environments. It's fast, flexible & robust. Built-in collision detection.
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This library is an effort to provide a collision detection library for generic polyhedra. Its purpose is mainly for 3D games where accurate detection is needed between two non-simple objects.
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StarlingPunk
StarlingPunk is a framework built on top the Starling library
StarlingPunk is a game framework built on top of the Starling GPU-accelerated 2D library (AS3 / Flash / AIR). It is inspired by FlashPunk: it gives structure (entities, worlds), collision detection systems, tile maps, etc., and is intended to help developers organize 2D game code more cleanly while benefiting from Starling’s performance. It has features for quick prototyping and reusing code between projects. Organizing game objects into Worlds, Entities, with type-based grouping etc. Manage entity drawing order via depth/layer so that scenes render properly in order (foreground/background, etc.)
