Python - OpenCV and PyQt5 together
Updated 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 52 lectures • 8h 14m | Size: 3.85 GB
Updated 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 52 lectures • 8h 14m | Size: 3.85 GB
Create desktop App with image processing techniques and Machine Learning Algorithms.
What you'll learn
Learn to use OpenCV and PyQt5 together with Machine Leaning
OpenCV - I/O scripts, drawing on image, save video from webcam
OpenCV - Histogram, Thresholding, Converting to another color space
OpenCV - Features detection, counting objects in image, Hough Transform
OpenCV - SIFT algorithm
PyQT5 - MainWindow, Menubar, Toolbar, Statusbar, Layouts, Linking to CSS
PyQt5 - Menus & Functions, Displaying image, perform actions on the image
PyQt5 - Messagebox, information & question
Machine Learning - Subdivision, overview
Machine Learning - Classification, Regression, Clustering
Machine Learning - The way to choose an Algorithm
Machine Learning - KNN & K-means demonstration
Machine Learning - Detection & Classification of objects on an image
Detection & Classification of objects on live video
Requirements
Time & desire to learn
A working computer :)
Python basics is a plus
Description
Learning from videos is one of the best way to learn! This course explains basics and advanced topics in OpenCV library that is used for machine vision, and also PyQt5 to create real Desktop App with Machine Learning Algorithms. A short overview on some Machine Learning Algorithms explained with pros and cons of each of them. After this knowledge, you should be able to create other applications with UI, processing images, and with Machine Learning algorithm either for classification, regression or clustering. With some basics in Python, you will understand every single coma in the videos. The course is made to be for 'All Levels', so everyone should understand everything without basic knowledge on libraries that are used. However, as it is said several times in the videos, it is a better way to go by learning a language before leaning a library. This tutorial is made to help, remember that it could help someone else even though it does not help a particular group.
Who this course is for
Anyone that is interested on how machine learning works.
Anyone that is interested on image preprocessing.
Anyone that wants to build Desktop App with Python
Python developers / Desktop or Web App developers curious about data science