This is the code repository for Computer Vision Projects with Python 3 [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
The Python programming language is an ideal platform for rapidly prototyping and developing production-grade codes for image processing and computer vision with its robust syntax and wealth of powerful libraries.
This video course will start by showing you how to set up Anaconda Python for the major OSes with cutting-edge third-party libraries for computer vision. You’ll learn state-of-the-art techniques to classify images and find and identify humans within videos.
Next, you’ll understand how to set up Anaconda Python 3 for the major OSes (Windows, Mac, and Linux) and augment it with the powerful vision and machine learning tools OpenCV and TensorFlow, as well as Dlib. You’ll be taken through the handwritten digits classifier and then move on to detecting facial features and finally develop a general image classifier.
By the end of this course, you’ll know the basic tools of computer vision and be able to put it into practice.
- Install and run the major computer vision packages within Python
- Apply powerful support vector machines for simple digit classification
- Understand deep learning with TensorFlow
- Work with human faces and perform identification and orientation estimation
- Build a deep-learning classifier for general images
To fully benefit from the coverage included in this course, you will need:
This video course is for programmers already familiar with Python who want to add computer vision and machine learning algorithms to their toolbox.
This course has the following software requirements:
This course has been tested on the following system configuration: ● OS: Windows 10 ● Processor: Intel i7 4th generation mobile ● Memory: 32 GB ● Hard Disk Space: 1 TB ● Video Card: GeForce GTX 970m