#Chessboard pdf open cv face detection install#
#Chessboard pdf open cv face detection code#

The color of an image can be calculated as follows: Number of colors/ shades = 2^bpp where bpp represents bits per pixel. In order to be processed by a computer, an image needs to be converted into a binary form. You can think of pixels to be tiny blocks of information arranged in the form of a 2 D grid, and the depth of a pixel refers to the color information present in it. More the number of pixels in an image, the better is its resolution. You can either use Jupyter notebooks or any Python IDE of your choice for writing the scripts.ДЄn image is nothing but a standard Numpy array containing pixels of data points.

#Chessboard pdf open cv face detection install#

run pip install opencv-contrib-python if you need both main and contrib modules (check extra modules listing from OpenCV documentation).run pip install opencv-python if you need only main modules.Packages for standard desktop environments (Windows, macOS, almost any GNU/Linux distribution) Unofficial pre-built OpenCV packages for Python. Please refer to the detailed documentation here for Windows and here for Mac.Дў. It can be installed in either of the following ways: OpenCV-Python supports all the leading platforms like Mac OS, Linux, and Windows. This makes it a great choice to perform computationally intensive programs.

#Chessboard pdf open cv face detection code#

OpenCV-Python is not only fast (since the background consists of code written in C/C++) but is also easy to code and deploy(due to the Python wrapper in foreground). You can think of it as a python wrapper around the C++ implementation of OpenCV. OpenCV-Python is the python API for OpenCV. OpenCV boasts of an active user base all over the world with its use increasing day by day due to the surge in computer vision applications. Although it is written in optimized C/C++, it has interfaces for Python and Java along with C++. OpenCV essentially stands for Open Source Computer Vision Library. The first release came a little later in the year 2000. OpenCV was started at Intel in the year 1999 by Gary Bradsky. Make sure that you have the following packages installed and running before installing OpenCV. Hands-on knowledge of Numpy and Matplotlib is essential before working on the concepts of OpenCV. With the advent of technology, face detection has gained a lot of importance especially in fields like photography, security, and marketing.

This technique is a specific use case of object detection technology that deals with detecting instances of semantic objects of a certain class (such as humans, buildings or cars) in digital images and videos. Face detection is a computer vision technology that helps to locate/visualize human faces in digital images.