Learn Computer Vision with Python and OpenCVEnglish | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 20m | 271 MBDetect and track objects in images and videos. Perform accurate and reliable processing tasks with Computer vision using OpenCVComputer 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.

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

What You Will LearnSet up and use OpenCV 3.3 with Python 3 from a Jupyter Notebook within a Docker containerPerform simple Computer Vision tasks using manipulation techniquesBuild Instagram-style image filtersAdjust brightness, saturation, and image hue to create Instagram-style filtersBulk-apply image manipulation operations to a folder of imagesSeparate moving foreground objects from the background of a videoTrack objects in a videoWork with binary images and use morphological operations and contours to extract colored objects from an image