OpenCV (Open Source Computer Vision Library) is an open source library for computer vision.
For years this library has been the point of reference for all passionate and expert of this discipline. Now in version 4.x, this library has more than 2500 algorithms inside, which over the years have been optimized.
These algorithms allow you to detect faces within an image or video, to identify objects, and to classify the actions performed by humans through videos. But not only that, videos and images can be analyzed in all their elements, characterizing the trace of the movements of the objects inside them, the extraction of three-dimensional models from these objects and many other applications.
The great success of this library has made it possible to attract the interest of thousands of experts in the sector, many of whom are making many contributions to improve the code and performance of this library.
The OpenCV library can support different languages including C ++, Java and Python with also interfaces to be able to use it on platforms like Matlab. In our site we will use the OpenCV library exclusively with Python.
Introduction to Edge Detection
Thresholding on an image
A method of detecting the vertices of an image
A method of detecting the edges of an image
OpenCV on Raspberry
Upcoming articles (in progress)
Changing the colors of spaces in an image
Watershed’s algorithm and image segmentation
The Grabcut algorithm