E1: Hello OpenCV
Objective
Get a computer vision library installed and test your video camera.
- Follow the instructions for installing OpenCV 3.4. The recommended setup for exercises is to use Python and Jupyter notebook. You should also install the extra opencv “contributed modules” for later exercises and your project.
-
Write code to load and display an image (e.g. PNG, JPG). You can use this helper function for displaying openCV images inline in a Jupyter notebook.
-
Write code to connect to your video camera, then capture and display a single frame of video.
-
(BONUS) Write code to display live camera frames.
Submit
Follow the submission instructions on the course information page. Include a screen capture of your captured webcam frame. In your solution notes, provide your operating system and camera model, any problems you ran into, and the main resource(s) you used (blog posts, online tutorials, stackoverflow posts, papers, textbooks, etc.). These resources should have brief descriptions of what the resource is and how it helped you.
You must combine your code, screen captures, and notes together into a single PDF. The best way to do this is by doing everything in a single Jupyter notebook using markdown cells for your notes and inline images for your output. Then just export as PDF.