Search Results for "opencv-2.4.6"
Sort By:
Showing 289 open source projects for "opencv-2.4.6"
View related business solutions-
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.
-
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
1
OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
2
opencv-mobile
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS
The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS, WebAssembly. This project provides the minimal build of opencv library for the Android, iOS and ARM Linux platforms. Packages for Windows, Linux, MacOS, and WebAssembly are available now. We provide prebuild binary packages for opencv 2.4.13.7, 3.4.18, and 4.6.0. We also provide prebuild binary package for iOS with bitcode enabled, that the official package lacks. -
3
OpenCV
Open Source Computer Vision Library
...Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html -
4
emgucv
Cross platform .Net wrapper to the OpenCV image processing library
Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages. The wrapper can be compiled by Visual Studio and Unity, it can run on Windows, Linux, Mac OS, iOS and Android. -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
5
SikuliX
SikuliX version 2.0.0+ (2019+)
SikuliX automates anything you see on the screen of your desktop computer running Windows, Mac or some Linux/Unix. It uses image recognition powered by OpenCV to identify GUI components and can act on them with mouse and keyboard actions. This is handy in cases when there is no easy access to a GUI's internals or the source code of the application or web page you want to act on. -
6
opencvsharp
OpenCV wrapper for .NET
OpenCV wrapper for .NET. Some Docker images are provided to use OpenCvSharp with AppEngine Flexible. The native binding (libOpenCvSharpExtern) is already built in the docker image and you don't need to worry about it. OpenCvSharp won't work on Unity and Xamarin platform. For Unity, please consider using OpenCV for Unity or some other solutions. -
7
GoCV
Go package for computer vision using OpenCV 4 and beyond
GoCV gives programmers who use the Go programming language access to the OpenCV 4 computer vision library. The GoCV package supports the latest releases of Go and OpenCV v4.5.4 on Linux, macOS, and Windows. Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. ... -
8
AIMr
The best AI Aimbot for Fortnite, Valorant, CS2, R6, COD, Apex, & more
...AIMr also provides visual customization options like field-of-view displays and detection indicators, allowing players to tailor their interface. The system is compatible with games that use human-shaped models, and although it functions effectively out of the box, optimizing it with CUDA-accelerated OpenCV is recommended for maximum performance. -
9
JavaCV
Java interface to OpenCV, FFmpeg, and more
JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, FlyCapture, Spinnaker, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, flandmark, Leptonica, and Tesseract) and provides utility classes to make their functionality easier to use on the Java platform, including Android. JavaCV also comes with hardware accelerated full-screen image display (CanvasFrame and GLCanvasFrame), easy-to-use methods to execute code in parallel on multiple cores (Parallel), user-friendly geometric and color calibration of cameras and projectors (GeometricCalibrator, ProCamGeometricCalibrator, ProCamColorCalibrator), detection and matching of feature points (ObjectFinder), a set of classes that implement direct image alignment of projector-camera systems (mainly GNImageAligner, ProjectiveTransformer, ProjectiveColorTransformer, ProCamTransformer, and ReflectanceInitializer), and more. -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
10
VidGear
A High-performance cross-platform Video Processing Python framework
VidGear is a high-performance Python framework that provides a unified and extensible solution for building real-time video processing applications. It acts as an abstraction layer over powerful multimedia libraries such as OpenCV, FFmpeg, and ZeroMQ, simplifying complex workflows into concise and efficient APIs. The framework is built around modular components called “gears,” each responsible for tasks such as video capture, streaming, encoding, and network transmission. It supports multi-threaded and asynchronous operations, enabling low-latency processing and efficient handling of high-throughput video streams. ... -
11
AI YouTube Shorts Generator
A python tool that uses GPT-4, FFmpeg, and OpenCV
AI-YouTube-Shorts-Generator is a Python-based tool that automates the creation of short-form vertical video clips (“shorts”) from longer source videos — ideal for adapting content for platforms like YouTube Shorts, Instagram Reels, or TikTok. It analyzes input video (whether a local file or a YouTube URL), transcribes audio (with optional GPU-accelerated speech-to-text), uses an AI model to identify the most compelling or engaging segments, and then crops/resizes the video and applies... -
12
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. -
13
Sherloq
An open source digital image forensic toolset
...The project emphasizes transparency and community collaboration, contrasting with proprietary forensic tools that often rely on secrecy. Initially developed in C++ in 2015 and later transitioned to a Qt-based GUI in 2017, Sherloq has since been ported to Python with PySide2, Matplotlib, and OpenCV to improve accessibility and ease of development. Its interface allows users to inspect images with real-time zoom, metadata exploration, noise analysis, and specialized algorithms for detecting forgeries and manipulations. -
14
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. It also provides event recording, snapshot management, and searchable video history to improve home or small-business security workflows. ... -
15
LearnOpenCV
C++ and Python Examples
...The repository supports beginners and advanced practitioners by offering reproducible code that demonstrates real-world computer vision techniques. Many examples integrate popular frameworks like PyTorch, OpenCV, and ONNX to reflect modern AI workflows. Overall, LearnOpenCV functions as a comprehensive applied learning hub for developers building expertise in computer vision and AI. -
16
GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even better GoogleTest. ... -
17
Computer Vision in Action
A computer vision closed-loop learning platform
Computer Vision in Action is a practical, example-rich repository that demonstrates real-world applications of computer vision techniques and algorithms in Python, often using OpenCV, deep learning models, and related tooling. It serves as a hands-on companion for learners and engineers who want to understand not just the theory, but how computer vision is actually implemented for tasks like object detection, image classification, feature tracking, optical flow, and image segmentation. The repository includes structured code examples, scripts, and notebooks that cover pipeline construction, preprocessing, model inference, and visual output rendering, making it easy for newcomers or intermediate practitioners to adapt patterns to their own projects. ... -
18
Simd Library
C++ image processing and machine learning library with using of SIMD
The Simd Library is a free open-source image processing and machine learning library, designed for C and C++ programmers. It provides many useful high-performance algorithms for image processing such as pixel format conversion, image scaling and filtration, extraction of statistical information from images, motion detection, object detection and classification, neural networks. The algorithms are optimized with using of different SIMD CPU extensions. In particular, the library supports the... -
19
VideoPipe
A cross-platform video structuring (video analysis) framework
...The framework is designed to be lightweight and portable, with minimal dependencies compared to other video processing systems, making it easier to deploy across different environments. It supports multiple inference backends, including OpenCV DNN, TensorRT, PaddleInference, and ONNXRuntime, allowing developers to choose the most suitable runtime for their performance and hardware requirements. VideoPipe also supports various video input sources such as RTSP, RTMP, and local files, enabling it to handle real-time streaming and batch processing scenarios. -
20
ProjectLearn.io
A curated list of project tutorials for project-based learning
...Each project entry typically links to external tutorials that guide learners through building a working application using modern frameworks and programming languages. Technologies covered include widely used tools such as React, Node.js, Flutter, TensorFlow, OpenCV, and other contemporary development platforms. By emphasizing hands-on learning, the repository encourages learners to strengthen their programming skills through real implementations rather than isolated coding exercises. -
21
Open Model Zoo
Pre-trained Deep Learning models and demos
...In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. Tools in the repository also help automate model downloads and other tasks, making it easier to incorporate these models into production systems or custom solutions. -
22
AppTestStudio
Automate your apps, games, and Android emulators
AppTestStudio (ATS) is an automated development environment, you can build, test, and automate Windows applications and android emulators. Quickly and interactively create automated actions by building Events either with pixel color matching, or using OpenCV image matching. Then attach actions to the events such as clicking or dragging. The multi processing (multiple scripts at the same time) was removed now only a single script can be run at one time. It was too confusing for some users which made the experience frustrating. If multiple concurrent scripts are needed just run an additional instance of ATS. ... -
23
OpenFace Face Recognition
Face recognition with deep neural networks
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google,... -
24
ArUco
Augmented reality library based on OpenCV
ArUco is a minimal library for Augmented Reality applications based exclusively on OpenCV. Relies on b/w markers with codes that are detected by calling a single function. Trivial integration of your augmented reality applications with OpenGL and OGRE. See documentation at https://drive.google.com/file/d/1OiavRVYVJ-WH88sQg1LUsh8CuJZUQyrX/view?usp=sharing -
25
Synapse Machine Learning
Simple and distributed Machine Learning
...SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. SynapseML also brings new networking capabilities to the Spark Ecosystem. With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster.
