Computer Vision: Neural Transfer Style & Green Screen Effect

4.1
별점
33개의 평가
제공자:
Coursera Project Network
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학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

How Neural Transfer Style works on Images

How Neural Transfer Style works on Videos, both recorded and live

How to mix two Images with the Green Screen Effect

Clock1 hours/week
Intermediate중급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

개발할 기술

OpencvPython ProgrammingJupyter Notebook

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

    안내형 프로젝트 진행 방식

    작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

    분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

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