Python 3.x for Computer Vision

This video course is a practical guide for developers who want to get started with building computer vision applications using Python 3. The video is divided into six sections:

• The Fundamentals of Image Processing
• Applied Computer Vision
• Object detection
• Making Applications Smarter
• Extending your Capabilities using OpenCV
• Getting Hands on

Throughout this video course, three image processing libraries: Pillow, Scikit-Image, and OpenCV are used to implement different computer vision algorithms.

The course will help you build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we look at in the course are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet.

About the Author

Saurabh Kapur is a computer science student at Indraprastha Institute of Information Technology, Delhi. His interests are in computer vision, numerical analysis, and algorithm design. He often spends time-solving competitive programming questions. Saurabh also enjoys working on IoT applications and tinkering with hardware. He likes to spend his free time playing or watching cricket. He can be reached at [email protected].