Introduction to OpenCV Python Tutorials¶
Getting Started with OpenCV-Python
- OpenCV is a huge open-source library for computer vision, machine learning, and image processing.
- It can process images and videos to identify objects, faces, or even the handwriting of a human.
- OpenCV was started at Intel in 1999 by Gary Bradsky
- Currently OpenCV supports a wide variety of programming languages like C++, Python, Java etc
- OpenCV is available on different platforms including Windows, Linux, OS X, Android, iOS etc
- Computer-Vision is playing a major role in self-driving cars, robotics as well as in photo correction apps.
OpenCV-Python¶
OpenCV-Python is a library of Python bindings designed to solve computer vision problems. OpenCV-Python makes use of Numpy, which is a highly optimized library for numerical operations with a MATLAB-style syntax. All the OpenCV array structures are converted to and from Numpy arrays. This also makes it easier to integrate with other libraries that use Numpy such as SciPy and Matplotlib.
Applications of OpenCV¶
There are lots of applications which are solved using OpenCV, some of them are listed below
- face recognition
- Automated inspection and surveillance
- number of people – count (foot traffic in a mall, etc)
- Vehicle counting on highways along with their speeds
- Street view image stitching
- Video/image search and retrieval
- Robot and driver-less car navigation and control
- object recognition
- Medical image analysis
- Movies – 3D structure from motion
- TV Channels advertisement recognition
Installing OpenCV From Prebuilt Binaries¶
We will learn to setup OpenCV-Python in your Windows system.
Below Python packages are to be downloaded and installed to their default locations.
- Python3
- Numpy
- Matplotlib
- opencv-python
pip install opencv-python
import cv2