Advanced Image Processing – Build a Blackjack Counter [2017]
Code an app that detects and recognizes playing cards using Python and OpenCV.
- 2.6 Hours of Video
- Certificate of Completion
- Source Code
- Closed Captions
Benefits
- On-demand, 24/7 access
- 2.6 hours of video
- Certificate of completion
- Source code and PDF notes
- Closed captions
Overview
This course has been archived and is no longer supported. For our latest courses on computer vision, consider trying our evergreen curriculums with a 1-Year Unlimited Access Package.
In this course we’ll build an app that can detect and recognize playing cards using Python and OpenCV. This app will detect that there is a playing card in an image, it grab all the cards it finds and reorients them.
There are two main concepts that will be covered in this course. One of them is thresholding, which is a technique of image segmentation. The second one is contour detection.
Learning goals:
- Thresholding:
- Binary thresholding
- Inverted binary thresholding
- Contour detection:
- Curve approximation
- Contour hierarchy
- Polygon approximation
Frameworks and tools covered: Python 2.7 (updated for Python 3.6), Anaconda 5.2, NumPy 1.15, OpenCV 2.4.8 (updated for OpenCV-Python 3.4.2)
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Lessons
Requirements
This course builds up on the concepts covered in our course Learn Python Image Processing.
Python 3 is used in this course..
It is recommended to take this course as part of the Python Computer Vision Mini-Degree, which includes 8 courses on the fundamentals of coding with Python, and teaches core concepts in computer vision.
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