Talk is an introduction to OpenCV 4+ pythonic API. We are going to go through most popular methods that are used in image processing and computer vision apps. We will also explore new methods that have been added in the newest release of the package. No prior OpenCV knowledge is required to participate.
Intro & added value
Image processing and computer vision are gaining huge interest nowadays. Modern machine learning models very often take advantage of features calculated on images. The talk is an introduction to the most popular pythonic image processing package → OpenCV.
You will learn the most important concepts in computer vision, and see how these are applied on images. After this talk you will be ready to start your first computer vision project!
Topic a.k.a. come if you:
The talk is addressed to Data Scientists, Python Developers and Data Engineers that would like to see what OpenCV package offers and if it’s the right tool to learn. I will provide a lot of examples explaining how image/video processing and feature extraction can be done in OpenCV.
The type of talk
All code examples will be shared afterwards through GitHub repository. During the talk, presentation will be either done with the help of Jupyter Notebook or interactive slides (to simulate the programming process).
What you will learn
- Intro to key image processing methods, such as:
- thresholding techniques
- colorspace conversion
- contour detection
- image filtering
- morphological transformations
- arithmetic with images
- color histograms
- shape detection
- template matching
- new methods that have been added since the release of 4.0 version.
- How these methods are applied with the use of OpenCV 4+ api.
- Tips&tricks to speed up image processing and feature extraction development time.