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OpenCV v4.1.0 (MacOS)

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.

The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize 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, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 18 million. The library is used extensively in companies, research groups and by governmental bodies.

Along with well-established companies like Google, Yahoo, Microsoft, Intel, IBM, Sony, Honda, Toyota that employ the library, there are many startups such as Applied Minds, VideoSurf, and Zeitera, that make extensive use of OpenCV. OpenCV’s deployed uses span the range from stitching streetview images together, detecting intrusions in surveillance video in Israel, monitoring mine equipment in China, helping robots navigate and pick up objects at Willow Garage, detection of swimming pool drowning accidents in Europe, running interactive art in Spain and New York, checking runways for debris in Turkey, inspecting labels on products in factories around the world on to rapid face detection in Japan.

It has C++, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS. OpenCV leans mostly towards real-time vision applications and takes advantage of MMX and SSE instructions when available. A full-featured CUDAand OpenCL interfaces are being actively developed right now. There are over 500 algorithms and about 10 times as many functions that compose or support those algorithms. OpenCV is written natively in C++ and has a templated interface that works seamlessly with STL containers.

Documentation and Tutorials.

Changes:
version:4.1.0

April, 2019

Spring update for OpenCV 4.x has been released.

Highlights of this release:

DNN module:
Reduced peak memory consumption for some models up to 30%.
Inference Engine
Inference Engine 2018R3 is now a minimal supported version of IE.
Myriad X (Intel® Neural Compute Stick 2) is now supported and tested.
Automatic IR network reshaping for different inputs.
Improved samples to work with models from OpenVINO Open Model Zoo
New networks from TensorFlow Object Detection API: Faster-RCNNs, SSDs and Mask-RCNN with dilated convolutions, FPN SSD

Performance improvements:
More optimization using AVX2 instruction set.
Automatic runtime dispatching is available for large set of functions from core and imgproc modules.













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Downloads Views Developer Last Update Version Size Type Rank
416 733 opencv.org <img src="https://www.oldergeeks.com/downloads/gallery/thumbs/OpenCV1_th.png"border="0"> Jun 05, 2019 - 11:55 4.1.0 142.66MB ZIP 5/5, out of 3 Votes.
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OpenCV  v4.1.0  (MacOS)  

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