OpenCV Getting Started Guide (Opening)

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OpenCV Getting Started Guide (Opening) [Copy link]

Some netizens said they wanted to learn something about opencv. Then I will share two articles. What is opencv OpenCV is an open source library for image processing, analysis, and machine vision. Whether you are doing scientific research or commercial applications, opencv can be your ideal tool library because it is completely free for both. The library is written in C and C++ and can run on Windows, Linux, and Mac OSX systems. All the code in the library is optimized and has high computational efficiency because it is more focused on being designed as an open source library for real-time systems. Opencv is optimized in C language, and it runs faster on multi-core machines. One of its goals is to provide friendly machine vision interface functions so that complex machine vision products can be launched faster. The library contains more than 500 interface functions across industrial product inspection, medical image processing, security, user interface, camera calibration, 3D imaging, machine vision and other fields. At the same time, since computer vision and machine learning are inseparable, the library also contains some commonly used machine learning algorithms. Perhaps, many people know that image recognition and machine vision are used in the field of security. However, few people know that in aerial photos and street photos (such as Google Street View), it is necessary to rely heavily on machine vision technologies such as camera calibration and image fusion. In recent years, OpenCV has been very useful in the fields of intrusion detection, specific target tracking, target detection, face detection, face recognition, face tracking, etc., and these are just the tip of the iceberg of its applications. Today, researchers from major companies and scientific research institutions around the world jointly maintain and support the development of opencv open source libraries. These companies and institutions include: Microsoft, IBM, Sony, Siemens, Google, Intel, Stanford, MIT, CMU, Cambridge...

辛昕

Keep going, I hope there will be more practical tutorials.

高进

The OP insists! Looking forward to the follow-up

wsdymg

Thanks for sharing,

azhiking

Thanks for sharing~