STEM-APKS

Source Code for the YouTube Videos: OpenCV on the Raspberry Pi

Source Code for Playlist: OpenCV Programming with the Raspberry Pi Tutorials

Tutorial-1 How to Install OpenCV on the Raspberry Pi
Tutorial-2 How to transfer files to and from the Raspberry Pi
Tutorial-3 Display an image with Python and C++ on the Raspberry Pi
Tutorial-4 Rotate an image with Python and C++ on the Raspberry Pi
Tutorial-5 Apply noise to an image with C++ on the Raspberry Pi
Tutorial-6 Apply noise to an image with Python on the Raspberry Pi
Tutorial-7 Blending Images with C++ and Python on the Raspberry Pi
Tutorial-8 Video Capture with C++ and Python on the Raspberry Pi
Tutorial-9 Downsampling,Upsampling, Scaling Images with C++ and Python on the Raspberry Pi
Tutorial-10 Canny Edge Detecting Images with C++ on the Raspberry Pi
Tutorial-11 Canny Edge Detecting Images with Python on the Raspberry Pi
Tutorial-12 Color to HSV with C++ and Python on the Raspberry Pi
Tutorial-13 Create Trackbars with C++ and Python on the Raspberry Pi
Tutorial-14 Adding Images with C++ and Python on the Raspberry Pi
Tutorial-15 Splitting Image Channels with C++ and Python on the Raspberry Pi
Tutorial-16 Defining Regions of Interest(ROI) with C++ and Python on the Raspberry Pi
Tutorial-17 Detecting Pixels with given color with C++ on the Raspberry Pi
Tutorial-18 Detecting Pixels with given color with Python on the Raspberry Pi
Tutorial-19 Histogram Equalization of Pixel Values with C++ on the Raspberry Pi
Tutorial-20 Histogram Equalization of Values with Python on the Raspberry Pi

About the Raspberry Pi and OpenCV

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.

The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc.

OpenCV has more than 47 thousand people in their user community and an estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies.

The Raspberry Pi is a credit-card-sized single-board computer developed in the UK by the Raspberry Pi Foundation with the intention of promoting the teaching of basic computer science in schools. The Raspberry Pi has a Broadcom BCM2835 system on a chip (SoC), which includes an ARM1176JZF-S 700 MHz processor, VideoCore IV GPU, and was originally shipped with 256 megabytes of RAM, later upgraded to 512 MB. It does not include a built-in hard disk or solid-state drive, but uses an SD card for booting and persistent storage. The Foundation provides Debian and Arch Linux ARM distributions for download. Tools are available for Python as the main programming language, with support for BBC BASIC (via the RISC OS image or the Brandy Basic clone for Linux), C, Java and Perl.