Computer Vision for Robotics
This guide is for implementing Computer Vision in the robotics . If you have been involve in th robotics and to uplift your skill or make robot intelligence , this course can be beneficial for you .
All the code are found at : Github .
This Course syllabus is designed as follows :
Getting images form various source such as camera , video or images . Creating blank images and saving it for future usage
Represent Images in a suitable data format so , it can be processed easily . Mostly it is represented as n-d array using numPY .
Modifying Images for displaying different effects which are done in Image editing software . Changing color scheme , Bluring, smoothing and generating shapes
- Color Detection
- Contour Detection
- Line Detection
- Corner Detection
- Face Recognization
- Sub Image Detection
- Feature Detection
- Object Detection
Track object using Optical Flow , CamShift and meanShift
This control the motion of robot based on the basic object detection
- Line Following
- Lane Detection and Tracking
Computer Vision for Robotics course is a getting start with computer vision in robotics so , we can develop more intelligence machine to assist human race in future.
I hope to collaborate with you
Requirement and Resource
This guide requires basic understanding of python . You can check yourself at learn python programming for robotics
All the code are found at : Github .
1. Download Code
Download or clone the GitHub repository Download .
If you downloaded the zipped version, unzip the directory somewhere you can access it.
2. Installing python
This simulator work with python 2.7.X.
Linux, BSD and Unix users
You are probably lucky and Python is already installed on your machine. To test it type python on a command line.
If you have to install Python, just use the operating system's package manager or go to the repository where your packages are available and get Python.
Python doesn’t come prepackaged with Windows.
- Go to Python Download page .
- Download python 2.7.x version
- Double-click the icon labeling the file python-2.7.x.exe.
3. Running code
In order to run code , Just move to code directory and type
What is Computer Vision
Computer vision is the science of machines, robots, computer systems, and artificial intelligence analyzing images, recognizing objects, and acting accordingly.
In simple terms , In computer vision we extract data from images , videos, and high dimensional data and we make decision based on these data.
It is closely related to
- Signal Processing
- Machine Vision
- Data Science
- Machine Learning
- Artificial Intelligence
Steps Involved in Computer Vision for Robotics
Deep Learning Process
Python is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace.
pip is a package management system used to install and manage software packages written in Python. Many packages can be found in the default source for packages and their dependencies — Python Package Index. Python 2.7.9 and later, and Python 3.4 and later include pip by default
A color space is a specific organization of colors. In combination with physical device profiling, it allows for reproducible representations of color, in both analog and digital representations.
Thresholding is the simplest method of image segmentation. From a grayscale image, thresholding can be used to create binary images.
The analysis and manipulation of a digitized image, especially in order to improve its quality.
In digital photography, computer-generated imagery, and colorimetry, a grayscale or greyscale image is one in which the value of each pixel is a single sample representing only an amount of light, that is, it carries only intensity information.
Binary image is a digital image that has only two possible values for each pixel. Typically, the two colors used for a binary image are black and white. The color used for the object in the image is the foreground color while the rest of the image is the background color.
Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer and a scene. Optical flow can also be defined as the distribution of apparent velocities of movement of brightness pattern in an image.