Python Tutorial for Computer Vision and Face Detection with OpenCV

Computer Vision is an AI based, that is, Artificial Intelligence based technology that allows computers to understand and label images. Its now used in Convenience stores, Driver-less Car Testing, Security Access Mechanisms, Policing and Investigations Surveillance, Daily Medical Diagnosis monitoring health of crops and live stock and so on and so forth…

A common example will be face detection and unlocking mechanism that you use in your mobile phone. We use that daily. That is also a big application of Computer Vision. And today, top technology companies like Amazon, Google, Microsoft, Facebook etc are investing millions and millions of Dollars into Computer Vision based research and product development.

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, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data.

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.

What you’ll learn

• Use OpenCV to work with image files
• Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
• Create Face Detection Software
• Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python
• Use Python and Deep Learning to build image classifiers
• Use Python and OpenCV to draw shapes on images and videos
• Create Color Histograms with OpenCV
• Study from MIT notes and get Interview questions
• Crack image processing limits by developing Applications.

#python #opencv #machine-learning #deep-learning #artificial-intelligence

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Buddha Community

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Deep Learning Project : Real Time Object Detection in Python & Opencv

Real Time Object Detection in Python And OpenCV

Github Link: https://github.com/Chando0185/Object_Detection

Blog Link: https://knowledgedoctor37.blogspot.com/#

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#python project #object detection #python opencv #opencv object detection #object detection in python #python opencv for object detection

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Well and Color Detection of PCR Plate using Python and OpenCV

Here’s how you can detect each well and it’s color in a PCR 96 well plate

OpenCV is an open source library aimed at computer vision. It has great features that make tasks such as object, and color detection simple and intuitive.

In order to detect each well’s color we need to first get each well’s position in the picture. So, our first goal is to detect each well in a PCR plate. Once we do that we can easily get the pixel colors inside those wells.

We will be working with these libraries:

• numpy
• KDTree
• webcolors
• cv2

#pcr #python #object-detection #opencv #computer-vision #well and color detection of pcr plate using python and opencv

Morse Code Translator Detect Blinks — Python, OpenCV, MediaPipe

Hello everyone,

It has been a while since the last time I posted a tutorial, or something in general. Basically life happened and I decided not to share rather than sharing low quality content. Today, I’ll walk you through a computer vision project that takes your live video input and translates your blinks into Morse Alphabet so you can blink short and long to write messages.

The source code for the project is here, I also used this awesome tutorial as a boiler plate to start with, if you want to learn more about Computer Vision applications you can check the channel owner’s channel from the link I posted. So without further ado let’s dive right into it.

As for the beginning I want to explain MediaPipe library a little bit, “MediaPipe offers open source cross-platform, customizable ML solutions for live and streaming media.”, this definition is from their own website and explains what you can do with that library shortly and cleanly, they offer several other solutions that can run on different platforms and I’ll explain all of them in a different post in the future. The feature that we’ll use today is called “Face Mesh”, this solution provides us a face landmark map with the most important 468 landmarks that can be seen in a human’s face. Using that map we’ll calculate the ratio between some particular points in the face and with that information we’ll detect if the person on the camera blinked or not.

#python #opencv #mediapipe #computer-vision #morse code translator detect blinks — python, opencv, mediapipe #morse code translator detect blinks