YoVDO

Computer Vision: Neural Transfer Style & Green Screen Effect

Offered By: Coursera Project Network via Coursera

Tags

Computer Vision Courses Python Courses OpenCV Courses Jupyter Notebooks Courses

Course Description

Overview

In this 1-hour long project-based course, you will learn how to do Computer Vision on images and videos with OpenCV and Python using Jupyter Notebook. You will understand how Neural Transfer Style works and you'll use it on images and on videos. Finally, you'll learn how to use the Green Screen Effect on your images.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and OpenCV pre-installed.

Prerequisites:
In order to be successful in this project, you should have an intermediate knowledge of Python and OpenCV.

Notes:
- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Taught by

Ilias Papachristos

Related Courses

2D image processing
Higher School of Economics via Coursera
Analyzing Video with OpenCV and NumPy
Coursera Project Network via Coursera
Basics in computer vision
Higher School of Economics via Coursera
Computer Vision - Object Detection with OpenCV and Python
Coursera Project Network via Coursera
Computer Vision - Object Tracking with OpenCV and Python
Coursera Project Network via Coursera