OpenCV

Learn how OpenCV-Python bindings are generated from C++ headers. We cover CV_EXPORTS_W, CV_WRAP, and other macros, plus the gen2.py generator and hdr_parser.py header parser scripts.

Learn to setup OpenCV-Python in Windows. Covers quick installation from prebuilt binaries and building from source using CMake and Visual Studio.

Learn to setup OpenCV-Python in Fedora using pre-built binaries or building from source. Includes CMake configuration, GCC setup, optional dependencies like TBB and Eigen.

Learn to setup OpenCV-Python in Ubuntu using two methods: installing from pre-built binaries or compiling from source. Step-by-step guide tested on Ubuntu 16.04 and 18.04.

The recommended way for most users to get OpenCV in Python: install from PyPI with pip. Covers virtual environments, platform notes, PyPI package variants, and common troubleshooting.

Learn to use Haar Cascade classifiers in OpenCV for face and eye detection. This tutorial covers the theory behind Haar features, integral images, AdaBoost, and cascade classifiers.

Learn how to generate and display HDR images from an exposure sequence in OpenCV. We cover Debevec, Robertson, and Mertens exposure fusion algorithms with camera response function estimation.

Learn how to remove small noises, strokes, and damage from old photographs using OpenCV's cv.inpaint(). We cover the Telea and Navier-Stokes inpainting algorithms.

Learn about Non-local Means Denoising algorithm to remove noise from images using OpenCV. We cover cv.fastNlMeansDenoising(), cv.fastNlMeansDenoisingColored(), and multi-frame denoising.