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Ex1: Create a web site for your homework
Ex1: Create a web site for your homework
- All of the home works in this course should be submitted to a web site created by you.
- Go to google sites "http://sites.google.com/new", use your Google account to log in, and create a web site called: "XXX website for Computer Vision course".
- The teacher suggests the students to use the account of Fu Jen Univ.'s Google Apps.
Please see the FJU application page to know how to create a FJU Google account.
- The teacher suggests the students to use the account of Fu Jen Univ.'s Google Apps.
- Fill-in your web site
- Upload some of your personal pictures into your web site.
- Create four web pages: Home, HW navigation, HW-exercise, HW-reading, HW-programming.
- Deadline: 2018/03/05 24:00.
Please submit your web address by Google Classroom. - Samples(ML105-2): Stephanie, Tony, Daniel.
Ex2: Install OpenCV 3.4.x
Ex2: Install OpenCV 3.4.x
- Goal: Download and install OpenCV 3.4.x on your computer.
- Instructions
- Go to OpenCV's home page: http://opencv.org/, and download v3.4.x for Windows, MacOS or Linux.
- Windows installation: Installation in Windows, How to build applications with OpenCV inside the Microsoft Visual Studio
- MacOS/Linux installation: Using OpenCV with gcc and CMake, Installation in Linux.
- There are more tutorials of MacOS installation on Internet. Please GOOGLE it by yourself.
- Compile an OpenCV example code and run it.
- Readings
- Introduction to OpenCV
- Read the web page OpenCV 3.4
- Google search or Youtube search by yourself with the keywords: "OpenCV", "OpenCV Tutorial", ...
- Report: Create a web page with at most 1000 words (Chinese or English) and a lot of pictures to describe
- What is OpenCV
- What is new in OpenCV 3.4
- How do you install OpenCV (with screen captures)
- The OpenCV example (with screen captures of its running)
- Examples
- Note : for the students who already did this exercise, please study the machine learning/deep learning module of OpenCV, and write a report. It will be better to show an ML/DL example in your report.
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