OpenCV 4.5.4 Released, Look For Updated Features And Fixes
OpenCV 4.5.4 has been released. Open Source Computer Vision Library is an open-source computer vision and machine learning software library. The non-profit organisation OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilise and modify the code. Some of the release highlights include: 1. GSoC 2021 is over, and several projects have already been integrated: 8-bit quantisation in the dnn moduleImproved Julia bindingsSpeech recognition samplednn module optimisations for RISC-VTutorial about universal intrinsics and parallel_for usage 2. Improvements in the dnn module: New layers and models supportSome existing layers have been fixedSoft-NMS implementationSupported OpenVINO 2021.4.1 LTS release 3. Restored LineSegmentDetector implementation 4. Better debugging experience with gdb pretty printer and XCode Quicklook support The library has more than 2500 optimised algorithms, including a comprehensive set of classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognise faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognise scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people in the user communities and an estimated number of downloads exceeding 18 million. The library is used extensively in companies, research groups and by governmental bodies. Apart from these above-mentioned changes, several others have been introduced; one can find more about the same here. Along with well-established companies like Google, Yahoo, Microsoft, Intel, IBM, Sony, Honda, and Toyota that employ the library, many startups such as Applied Minds, VideoSurf, and Zeitera make extensive use of OpenCV.
It aims to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
It provides a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
["Machine Learning", "ml algorithms", "ML models", "OpenCV"]
["Go", "machine learning", "ml algorithms", "programming_languages:R", "ML models", "Machine Learning", "programming_languages:Go", "computer vision", "OpenCV", "Julia", "GAN", "R", "startup"]
["machine learning", "computer vision", "OpenCV", "R", "Go", "Julia", "GAN", "startup", "programming_languages:R", "programming_languages:Go"]
Kumar Gandharv, PGD in English Journalism (IIMC, Delhi), is setting out on a journey as a tech Journalist at AIM. A keen observer of National and IR-related news.