Python 3.x for Computer Vision

Course details

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.