Learn Python Computer Vision with OpenCV by Kiran A. Bendigeri

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 35 lectures (2h 55m) | Size: 1.31 GB

Course includes Python, Numpy, Matplotlib and OpenCV. Image processing and object detection from videos and images
What you'll learn:
Computer Vision using OpenCV
Image Processing - Translation, Rotation, Scaling, Brightness, Arithmetic Operations, Convolutions, Blurring, Sharpening and many more
Object Detection using Haar Cascade

Requirements
Be able to operate the computer.
High School Math.

Description
You are going to learn Computer vision using OpenCV and Python.

OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel). The library is cross-platform and free for use under the open-source Apache 2 License. Starting with 2011, OpenCV features GPU acceleration for real-time operations.

OpenCV is something which is of intermediate level in Python programming, But in this course as I start from basics of Python programming, even if you are a novice in programming you can take this course and start building applications.

I am covering the basics of Python, Numpy, Matplotlib, OpenCV and 3 Applications.

1) Python - Data types, Lists, Tuples, Dictionary, Sets, Class, Function

2) Numpy - Arrays and its use

3) Matplotlib - Charts

4) Image Processing using OpenCV - Translation, Rotation, Scaling, Greyscaling, Color Spaces, Image Pyramids, Brightness and Contrast, Cropping, Arithmetic Operations, Convolutions, Blurring, Sharpening, Threshold, Dilation and Erosion, Edge Detection, Contour, Shape Matching, Drawing Images, Finding Corners.

5) Projects :-

A) Live Video Sketch - Here we are taking a small video clip and covert the video into sketch. We are going to use previously learnt concept of greyscaling, edge detection etc

B) Object Detection - Detecting Objects from video. Using Haar cascade.

C) Face Detection - Detecting Face in an image.

You can develop full fledged Image processing application using this course. Also with this knowledge you can develop applications for security systems, classifying objects, converting old books to images, make it readable and so on.

Who this course is for
Everyone who want to build some interesting Computer Vision Applications.
Anyone who want to learn a new thing in Python Programming.
Students, Professinals, Hobbyists.