Description

Python 3.x for Computer Vision

Python 3.x for Computer Vision
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 311 MB Genre: eLearning | Language: English
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.

Welcome to the ultimate online course on Python for Computer Vision!

This course is your best resource for learning how to use the Python programming language for Computer Vision.

We’ll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data.

The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision.

Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more.

As the fastest growing language in popularity,

In this course we’ll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come.

Then will move on to using the

Then we’ll move on to understanding video basics with OpenCV, including working with streaming video from a webcam.  Afterwards we’ll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.

Then we’ll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We’ll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.