Creating your own sketch with OpenCV

Creating your own sketch with OpenCV

How often do you feel like getting yourself sketched by an artist? Well say no more, now you can easily make the use of OpenCV and make your own sketch within few minutes. Just in 4 steps OpenCV will provide you with the portrait of the same. Creating your own sketch with OpenCV

How often do you feel like getting yourself sketched by an artist? Well say no more, now you can easily make the use of OpenCV and make your own sketch within few minutes. Just in 4 steps OpenCV will provide you with the portrait of the same.

Okay let’s dive right into it and make yourself a sketch without picking up a brush.

So for this particular task we are going to use Google Colaboratory or “Colab” for short which allows you to write and execute Python in your browser with Zero configuration required, free access to GPUs and easy sharing.

Well, you can either use Jupyter Notebook for the same, it’s totally your call.

The four steps which we are going to use today are as follows:

  1. Converting an RGB colour image to a grayscale image.
  2. Convert the grayscale image to a negative.
  3. Smoothening the image using the Gaussian Blur.
  4. Dodging and burning the image to get the final output.

opencv computer-vision python

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

OpenCV Python Tutorial: Computer Vision With OpenCV In Python

OpenCV Python Tutorial: Computer Vision With OpenCV In Python: Learn Vision Includes all OpenCV Image Processing Features with Simple Examples. Face Detection, Face Recognition. Computer Vision is an AI based, that is, Artificial Intelligence based technology that allows computers to understand and label images. Use OpenCV to work with image files. Create Face Detection Software. Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python. Use Python and Deep Learning to build image classifiers. Use Python and OpenCV to draw shapes on images and videos. Create Color Histograms with OpenCV

OpenCV Python Tutorial - Computer Vision With OpenCV In Python

In this OpenCV Python Tutorial article, we will be covering various aspects of Computer Vision using OpenCV in Python. OpenCV has been a vital part in the development of software for a long time. Learning OpenCV is a good asset to the developer to improve aspects of coding and also helps in building a software development career.

Python OpenCV Tutorial - Learn Computer Vision with OpenCV and Python

Python OpenCV Tutorial - Learn Computer Vision with OpenCV and Python: Introduction to OpenCV and Image Processing in Python, Image processing basics, Object detection and tracking, Deep Learning, Facial landmarks and many special applications.

OpenCV Python for Beginners - Learn Computer Vision with OpenCV 2020

OpenCV Python for Beginners - Learn Computer Vision with OpenCV in 10 Hours (2020). You'll learn: Introduction to OpenCV; How to Install OpenCV for Python on Windows 10; How to Read, Write, Show Images in OpenCV; How to Read, Write, Show Videos from Camera in OpenCV; matplotlib with OpenCV; Image Pyramids with Python and OpenCV; Canny Edge Detection in OpenCV; Image Blending using Pyramids in OpenCV; Face Detection using Haar Cascade Classifiers ...

Create a Virtual Pen and Eraser with Python OpenCV - Genial Code

Learn Free how to create a virtual pen and eraser with python and OpenCV with source code and complete guide. This entire application is built fundamentally on contour detection. It can be thought of as something like closed color curves on compromises that have the same color or intensity, it's like a blob. In this project we use color masking to get the binary mask of our target color pen, then we use the counter detection to find the location of this pen and the contour to find it.