This is the code repository for Python 3.x for Computer Vision [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
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.
- Work with open source libraries such Pillow, Scikit-image, and OpenCV
- Write programs such as edge detection, color processing, image feature extraction, and more
- Implement feature detection algorithms such as LBP and ORB
- Understand Convolutional Neural Networks to learn patterns in images
This video course is for Python developers who want to perform image processing. It’s ideal for those who want to explore the field of computer vision and design and develop computer vision applications using Python. You are expected to have basic knowledge of Python.
This course has the following requirements:
Laptop or PC with Internet connection
Python basic programming skills