Learn Computer Vision with Python and OpenCV
Duration: 1h 20 | Video: h264, 1280x720 | Audio: AAC, 48kHz, 2 Ch | 271 MB
Genre: eLearning | Language: English

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Detect and track objects in images and videos. Perform accurate and reliable processing tasks with Computer vision using OpenCV

Video Description
Computer vision solves imaging problems that cannot be solved using ordinary systems and sensors. OpenCV is one of the most popular Computer Vision libraries and helps you write faster code.

This course begins with the basics of loading and working with images. You will detect colored objects in your images easily. You will also use tools to build and apply filters in your photos and track objects in a video.

By the end of the course, you will have a firm grasp of Computer Vision techniques using OpenCV libraries. This course will be your gateway to the world of data science.

The code bundle is placed at: https://github.com/PacktPublishing/Learn-Computer-Vision-with-Python-and-OpenCV-Video

Style and Approach
This course will teach you the skills required to develop computer vision applications using Python with practical examples.

What You Will Learn
Set up and use OpenCV 3.3 with Python 3 from a Jupyter Notebook within a Docker container
Perform simple Computer Vision tasks using manipulation techniques
Build Instagram-style image filters
Adjust brightness, saturation, and image hue to create Instagram-style filters
Bulk-apply image manipulation operations to a folder of images
Separate moving foreground objects from the background of a video
Track objects in a video
Work with binary images and use morphological operations and contours to extract colored objects from an image

Table of Contents
GET STARTED WITH OPENCV LIBRARIES
DETECT COLORED OBJECTS IN IMAGES
FEATURE DETECTION ALGORITHMS
VIDEO ANALYSIS