Search Results for "opencv-4.6.0"
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Showing 282 open source projects for "opencv-4.6.0"
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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. -
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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. -
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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">
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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. -
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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. -
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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. ... -
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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. -
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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. -
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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... -
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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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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. -
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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. ... -
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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... -
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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. -
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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. ... -
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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,... -
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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 -
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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. -
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JosVideoProject
This projects target is to handle image and video
This projects target is to handle images and videos from several sources. The central library used is OpenCV. This project is for learning, investigation and tinker with sourcecode for imaging. -
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Video Object Remover – Frame-Accurate
🎥 A free & open-source Python tool to remove unwanted objects from videos frame-by-frame using brush masking and AI inpainting (OpenCV + FFmpeg). EXE included.
Video Object Remover – Frame Accurate Edition is a free and open-source desktop application that helps you remove unwanted objects, logos, or watermarks from videos using brush-based masking and AI inpainting. The tool extracts video frames using FFmpeg, lets you mask objects frame-by-frame, and removes them using OpenCV. Built with Python and Tkinter, it features a modern dark-themed GUI, adjustable brush tool, zoom control, and real-time logging. The cleaned video is rebuilt and exported with original quality. Includes a precompiled Windows EXE for normal users (no Python required) and full source code for developers or students. Perfect for YouTubers, video editors, educators, and open-source enthusiasts... -
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photoStacker
Aligns and stacks astronomical images using point-set registration.
PhotoStacker aligns and stacks astronomical night sky images using Coherent Point Drift (CPD) for precise star alignment. This project leverages external tools like SExtractor for source extraction and OpenCV ORB for feature detection and matching. It includes custom binaries for detection, registration, and transformation, ensuring accurate image alignment. The workflow script automates the process, making it easy to stack images for enhanced astronomical photography. The project is ideal for astrophotographers seeking to improve image quality through stacking, utilizing robust algorithms and open-source tools. -
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image2relief
Create CNC G-code from images for gemstone engraving.
image2relief is a C++ program using OpenCV to convert raster images into G-code for CNC engraving of gemstones. It supports the creation of mid-reliefs, low reliefs, and shallow reliefs (without undercuts), using image-based surface profiling. The tool accounts for different end mill diameters by simulating circular tool footprints. The image is scanned stepwise along a customizable path. -
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COVA
Context-aware on-premise app for AI-resistant face anonymization
...It analyzes each face's pose and brightness, then picks the minimum blur or mosaic strength that still prevents re-identification, even against AI restoration tools like Real-ESRGAN and GFPGAN. Built with Python, PyQt5 and OpenCV, COVA runs fully on your local machine, making it ideal for CCTV, medical recordings, research datasets and broadcast content. Features include live Original/Anonymized preview, support for images and video, adjustable risk levels and attack models, and timeline graphs showing angle, brightness and anonymization strength. -
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MarkerMapper
A cost-effective localization system using planar squared markers
...The map generated can be used by ArUCO library for localizing your camera. The library depends on Aruco for the marker detection: https://www.uco.es/investiga/grupos/ava/portfolio/aruco/ It also depends on OpenCv and eigen3 (the later is included in the 3rdparty directory). -
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Imaging Instruments Lite
Image processing App for Windows Desktop
Imaging Instruments lite is a comprehensive image processing application developed following the Model-View-Controller (MVC) design pattern, utilizing Python, Tkinter, and OpenCV. It provides users with image manipulation capabilities, leveraging multi-threading with OpenMP and GPU acceleration using CUDA-C. Fueled by yerba mate and a passion for coding. Created by Agustin Tortolero. website: https://agustintortolero.pythonanywhere.com/ Source code: https://github.com/agustinTortolero/Imaging-Instruments-lite