Python, java, and c++. The first version of opencv, 1.0, was released in 2006 and the opencv community has grown by leaps and bounds ever since. Opencv-python is the python api for opencv. It is also compatible platforms, windows, mac os and linux. Keep in mind that in order to use this library optimally, you must have knowledge of: numpy library matplotlib library for the installation of opencv in python there are 2 ways: from binary files and precompiled source files : for this, each operating system must be consulted (for example , windows and mac os .
Through packages for standard desktop environments (windows, macos and almost any gnu/linux distribution): if only core modules are needed, run pip install opencv-python if both core and additional (contrib) modules are needed, run pip install opencv-contrib-python jupyter or any python ide can be used to write these commands. Images as arrays an e commerce photo editing service image is nothing more than a standard numpy array containing pixels of data points . The higher the number of pixels in an image, the better its resolution. You can think of pixels as little blocks of information arranged in the form of a 2d grid, and the depth of a pixel refers to the color information present in it.
To be processed by a computer, an image must be converted to a binary form . The color of an image can be calculated as follows: number of colors / shades = 2^bpp (where bpp represents bits per pixel) therefore, the more bits/pixel, the more colors possible in the images. The following table shows this relationship more clearly: bits per pixel let us now see the representation of the different types of images: binary image a binary image consists of 1 bit/pixel and therefore can only have