Open Source Computer Vision Libraries - Page 7
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Computer Vision Libraries
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MTCNN Face Detection Alignment
Joint Face Detection and Alignment
MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. Online hard sample mining to improve training robustness. -
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A photo gallery management system based on hand gesture recognition. You must make three color markers by yourself, which the red one on index of the right hand, the green one on thumb of the right hand and the blue one on index of the left hand.
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A library analog to those included in Matlab without the need of external libraries; just right for embedded or static linking. MTL was used to build a 3d Scanner. MTL consists of pars B - Basic Functions, Matrices, Images, Hypermodels (3d Models and up) N - Numeric Functions ranging from linear regression over nonlinear optimization to singular-value computation I - Image filters and Image enhancement H - Hardware related (optional part), does require additional libraries and is only useful on certain hosts. G - Hyper-Model functions such as ray-plane intersections etc.
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time. -
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This program utilize the OpenCV (Intel Computer Vision) library to track an initial point over a series of frames. The image source is a camera or a pair of before/after pictures. Each frame passes some filter stages. This pipeline can be configured.
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Mexopencv
Collection and a development kit of matlab mex functions for OpenCV
mexopencv is a collection of MEX functions that provide MATLAB bindings for OpenCV, the popular computer vision library. It enables MATLAB users to access nearly the full range of OpenCV’s C++ API directly from MATLAB, combining the ease of MATLAB scripting with the performance of OpenCV. -
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MingCV
Ming' Computer Vision library
Ming' Computer Vision C++/Python library -
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Monk Computer Vision
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection - https://github.com/Tessellate-Imaging/Monk_Object_Detection. Monk object detection is our take on assembling state of the art object detection, image segmentation, pose estimation algorithms at one place, making them low code and easily configurable on any machine. - Monk GUI - https://github.com/Tessellate-Imaging/Monk_Gui. An interface over these low code tools for non coders. -
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A C++ library of high level motion analysis/computer vision functions, coupled with GUIs that allow easy configuration and use. Current development focuses on color tracking, multiple camera calibration and triangulation, and 3D tracking algorithms.
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Myron (webcamxtra) brings native-implemented, cross-platform computer vision to Processing and Macromedia Director, allowing inexpensive commercial USB cameras to control just about anything. Keep computer vision easy and inexpensive for the people!
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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OSAR Appliances
The OSAR Linux Image for Augmented Reality and Computer Vision
The OpenSUSE Augmented Reality (OSAR) distribution is the first GNU / Linux appliance created for the exclusive development of applications with augmented reality technology and games with computer vision. -
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OSCON 13:Computer Vision Tutorial
Ubuntu 12.04.2 pre-installed with OpenCV 2.4.3 and tutorial codes
This is the material given to the attendees of OSCON-13 tutorial "Beginner's Guide to Computer Vision". The ISO contains a pre-installed Ubuntu 12.04.2 with OpenCV 2.4.3 and all the tutorial codes -
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OSVIACAM
OSVIACAM Linux for quadriplegic disabled
OSVIACAM is a linux image based on openSUSE aimed at quadriplegic disabled. The image is in beta, but features the key features to meet the need to operate an operating system without mouse and keyboard. The differential of the image is to rely on the application VIACAM that allows to move the mouse with only the movements of the face. -
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A .NET wrapper for OpenCV, a computer vision library. The wrapper is fully developed in C#, making the OpenCV library available to all the .NET based languages, like C#, VB.NET, managed C++, IronPython, F#, etc.
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OpenCV-AR is a software library used for Augmented Reality development. It is targeted on Linux, though it is also able to work on Windows platform. It is an alternative to ARToolKit for Augmented Reality application development.
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The Java parallel to the popular Intel computer vision library, OpenCV. OpenJCV = Open Java Computer Vision
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OpenTLD
OpenTLD is an open source library for real-time 2D tracking
OpenTLD is an open source implementation of the TLD (Tracking-Learning-Detection) framework, designed for real-time 2D tracking of a single object in video sequences. Because it fuses tracking and detection, TLD can recover from occlusions, drift, or failures by using its detection mechanism to reacquire the object. In terms of usage, one typically initializes the tracker by providing a bounding box on the first frame, then calls a function like run_TLD to process a video and obtain bounding boxes over time. The system updates its internal models as frames are processed, and can re-detect the target when tracking fails. The algorithm’s performance is known to improve over time due to its online adaptation behavior. Because of its age and MATLAB dependencies, adopting it in modern C++ / real-time pipelines may require effort (e.g. rewriting or porting) or using more recent tracking libraries. -
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The Tensor Voting Framework is a powerful technique for perceptual grouping, manifold learning, etc. It has proved to be a useful tool in the Computer Vision community. OpenTVF is an open source implementation of TVF.
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PanoramaServer
Open Source Panorama Server for free virtual tour of 360 degrees views
Ideal for creating virtual tours of panoramic views for all sorts including property exhibition for brokers at real estate agencies/property agents, tour guide for indoor/outdoor venues, information to public/private facilities for curators, travel journal for tourist as log book, backdrop setting for storytelling, treasure hunt like games, big data mining for pattern through computer vision in artificial intelligence, etc. It is like creating your own Google Map Street View. All is required by the user is to have photos of equirectangular format (panorama) taken from 3D cameras common for on-site premises. These images can be referenced by the PanoramaServer to create virtual travels with 360 degrees view where viewers can navigate to different locations, view information, etc. If made available online to general public over the internet, can even share the link of your virtual trips. PanoramaServer is free as it is open source licensed. -
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Panzer Combat II
Computer-assisted miniature tank game.
Panzer Combat II is a multi-player voice and webcam enabled computer-assisted distributed miniature wargame of World War II tank combat. Firing is done by placing a webcam behind the aiming unit. Distance to target is computed using computer vision. Action inside the tanks is performed on the computer screen while battlefield strategy is played on the miniature terrain. Both camps can use a different laptop or tablet, the game will interconnect. You can try it online : http://server.panzercombat.com/PCII_Web/move.htm Look at battle reports : http://www.flickr.com/photos/panzercombatii Or watch a demo : http://www.youtube.com/watch?v=WcjfV8Odtss 100% CLEAN : http://games.softpedia.com/progClean/Panzer-Combat-II-Clean-95530.html -
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Papier-Mâché is a toolkit for building tangible user interfaces that employ computer vision, RFID tags, and/or bar-codes.
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Phi-3-MLX
Phi-3.5 for Mac: Locally-run Vision and Language Models
Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips. -
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Proposed is an algorithm that uses computer vision, combined with a modified Rubine classifier, to allow arbitrary N-sided polygons as accepted sketches in real-time.
