Search Results for "opencv video"
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Showing 46 open source projects for "opencv video"
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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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Delphi-OpenCV
Project Delphi-OpenCV. Translation of OpenCV library header files
Delphi-OpenCV is a set of Object Pascal bindings and tools that bring OpenCV functionality into the Delphi development environment. It provides access to computer vision capabilities such as image processing, feature detection, and video analysis within native Delphi applications. The project includes sample programs, preconfigured packages, and integration with related libraries like SDL and OpenGL. -
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OpenCV
Open Source Computer Vision Library
The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. 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!... -
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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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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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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. -
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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. -
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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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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... -
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MarkerMapper
A cost-effective localization system using planar squared markers
This project allows the creation of cost-effective camera localization systems based on squared planar markers you can print at home. Print the markers, place them in the environment and record a video or take pictures of them. This project analyzes the images and returns the 3D location of the markers: the marker map. 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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AI-Shorts-Creator
Python-based tool that leverages the power of GPT-4
AI-Shorts-Creator is a Python-based tool that automates the creation of short-form videos by analyzing long-form content and extracting the most engaging segments. It uses AI models to evaluate transcripts and identify highlight moments, then processes video clips accordingly. The system integrates FFmpeg and OpenCV to crop videos dynamically, often using face detection to keep subjects centered. It is designed for content creators who want to generate short videos quickly without manual editing. The workflow includes downloading source videos, analyzing content, segmenting highlights, and exporting finished clips. ... -
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Easy Upscale
A simple image upscaler application using EDSR, ESPCN, FSRCNN, etc.
This application was made to fulfill the assignment for the Data Structures course. The concept of the application is an application to upgrade/enhance image quality. The main theme is queues, we implement circular queues for pooling/storing a list of images to be upscaled. Gui creation is made manually using the tkinter library. For the upscale process itself, it uses the OpenCV library with a model obtained from open source. Checked using vermin. Minimum required versions: 3.6 Incompatible... -
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Face Mask Detection
Face Mask Detection system based on computer vision and deep learning
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. ... -
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Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
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opencv4nodejs
Nodejs bindings to OpenCV 3 and OpenCV 4
OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition. -
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raspicam
C++ library for controlling Raspberry Pi Camera (with/without OpenCV)
This library allows to use the Raspberry Pi Camera. Main features: - Provides class RaspiCam for easy and full control of the camera - Provides class RaspiCam_Cv for easy control of the camera with OpenCV. - Easy compilation/installation using cmake. - No need to install development file of userland. Implementation is hidden. - Many examples -
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DCVGAN
DCVGAN: Depth Conditional Video Generation, ICIP 2019.
This paper proposes a new GAN architecture for video generation with depth videos and color videos. The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical... -
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The Integrating Vision Toolkit (IVT) is a powerful and fast C++ computer vision library with an easy-to-use object-oriented architecture. It offers its own multi-platform GUI toolkit. OpenCV is integrated optionally. Website: http://ivt.sourceforge.net
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EmguCv410 Face Recognition Detect
EmguCv C# OpenCv Cuda Face Recognition + Gender, Emotion, Ethnicity
The site says "Malware detected but NOT TRUE", it's just encrypted! EmguCvSharp Face Detection Full source code: https://sourceforge.net/projects/emgucvsharp-live-face-detect/ . if (CudaInvoke.HasCuda) //THE CODE TO USE CUDA . Emgucv Gender detection Emgucv Emotion detection Emgucv Ethnicity detection Emgucv Face Recognition also includes Pedestrian detection For Live: Face Attendance System, Facial Emotion, Gender Recognition Security... -
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Delphi Face Recognizer
Delphi Face Recognizer
...mail: dbinXecod@gmail.com if the link is broken here: https://www.paypal.me/dBinXecod/184 Added Feature: X. IP Camera RTSP Connections Real RTSP url link test Real MJPEG url link test Y. Capture faces from Video File Last bug FIXED April_08_2019_12.24pm, X. Recognized Faces Better Bug fixes: xxx Gate ID Multi Face Recognition: $384 (via this HARDCORE Face Recognition) https://sourceforge.net/projects/opencv-multi-face-detect/ C++Builder: https://sourceforge.net/projects/cbuilder-face-recognizer/ -
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Calyp
Calyp is an open-source raw video player for image/video analysis
Calyp is an open-source raw video player developed using the C++ Qt libraries. This is the new version of the playuver. New name new features coming. For Ubuntu and Debian based distributions use our Personal Package Archive (PPA): ppa:pixlra/ppa -
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VideoMan Library
C++ library for image acquisition and visualization
Library for capturing video from cameras, 3d sensors, frame-grabbers, video files and image sequences. It can also display multiple images using OpenGL with different layouts. Easy integration with OpenCV, CUDA... Perfect for computer vision. Keywords: video capture, computer vision, machine vision, opencv, opengl, cameras, video input devices, firewire, usb, gige -
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Face Recognition
World's simplest facial recognition api for Python & the command line
Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a... -
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Este proyecto utiliza el traincascade (nueva version de haarcascade) de OpenCV para clasificar los autos que se encuentran en la calle. Dependiendo de una linea imaginaria que esta en la calle, se puede saber si el vehiculo esta en movimiento o estacionado, y de esta manera contabiliza las mismas y las muestra en el frame del video.
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Eye Connect
The first free cross-platform HCI for upper body paralysis.
...Both systems are integrated into Eye Connect, a free suite of user-friendly software designed to provide full system control through facial feature detections. Watch the video: https://www.youtube.com/watch?v=LowRaG3dflA Requirements: - A Linux, Windows or Mac environment. - A Python 2.0 Installation - A webcam - the OpenCV library - The pyuserinput library
