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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.

Easily collect, transform, and transfer vehicle data to the cloud in near-real-time. AWS IoT FleetWise makes it easy and cost-effective for automakers to collect, transform, and transfer vehicle data to the cloud in near-real-time and use it to build applications with analytics and machine learning that improve vehicle quality, safety, and autonomy. Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles....

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime,...

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! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html

A library and associated tools for building and searching with Active Shape Models (ASM). It builds on the VXL computer vision libraries. Includes a GUI tool to search new images with the ASM. Depends on: VXL, Qt (Version 4), UoMqVXL

butteraugli is a perceptual similarity metric designed to estimate how noticeable differences between two images will be to the human eye. Instead of simple pixel math, it models aspects of human vision—color sensitivity, spatial masking, and contrast perception—to highlight differences that viewers actually see. The core tool outputs a single “distance” score along with per-pixel or per-region maps that show where artifacts are most objectionable. These maps make it practical to tune...

QCV is a Qt-based computer vision framework library that provides an easy to use interface to display, analyze and run computer vision algorithms. The library is provided with practical examples to show what you can do with just a few lines of code. OpenCV is used as the supporting computer vision library. QCV provides interfaces for C and C++. The C interface is a set of simple function calls to allow the user to visualize data and obtain events from the system and user input. The...

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.

The goal of cvtk is to provide an easy to use computer vision framework that allows real-time tracking of color-marked objects in 2 dimensions.