PDF OpenCV Computer Vision with Python

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OpenCV Computer Vision with Python
Contents:
  1. Moving Object Detection Using Opencv Python
  2. Motion history image opencv python
  3. OpenCV Complete Dummies Guide to Computer Vision with Python
  4. See a Problem?

Then later on, we will go ahead with Optical Character Recognition, which is also an Artificial Intelligence based application Optical Character Recognition is an old Technology actually. It has recently been improved. We will be using a library called Tesseract, which is also an OpenCV based library. We will be using that and perform Optical Character Recognition quickly, without having to deal with all the other complexities, since that library makes the Optical Character Recognition very easily to do within your Python program.

Also real time object detection from webcam using SSD you may use the same technique for other models too. And by the end of this course, we will providing you with a course completion certificate which you can keep with you an mention it in your portfolio so that you will be having more weightage , when you are dealing with jobs based on Computer Vison Technology.

So without wasting much time, lets dive in to this magical world. See you soon in the class room. Have a great time. Bye Bye. We use cookies to make interactions with our websites and services easy and meaningful. For more information about the cookies we use or to find out how you can disable cookies, Click Here. Notify Me. Main Menu Explore. Remember me. Forgot Password? Log in. Not a Member? Sign up. Already a Member? Offer Price:. Original Price:. You Save:. Add To Cart. Continue Shopping. Redeem coupon Coupon Applied. What it includes?

Lifetime Access. No Limits! Certificate of Completion. About this Course Hello and let me welcome you to the magical world of Computer Vision. Even to analyze data coming from outer space stars, planets etc also we use Computer Vision.

Moving Object Detection Using Opencv Python

Here are the major topics that we are going to cover in this course. Session 2: Installing Virtual Box and Ubuntu 18 In the second session, we will be installing a Virtual Box with Ubuntu 18 the latest version of Ubuntu Linux in it, so that we can have our Computer Vision based laboratory setup separately, rather than we need to install all the packages and everything into our computer or laptop that you are using daily.

Session 3: Installing Libraries and Dependencies And in the third session, we will be installing the libraries that are required for Computer Vision Programming. Session 5: Image Processing Concepts In the next session, which is a Theory session, we will have the concepts, the Pixels, Size, Image and all the concepts that are based on Image Processing. Session 7: OpenCV Pixel and Area Manipulation Then in the next session, we will manipulate the image based on its pixels, that is the finest element available for that image that is the pixel.

Session 8 - OpenCV - Drawing Lines, Rectangles, Simple, Concentric Circles, Random Circles In the coming session, we will draw some shapes, some rectangles, circles, shapes like that we will try to draw on top of our image using OpenCV library. Session 11 - OpenCV Image Transformation - Translation, Rotation, Resizing, Flipping, Cropping And then the next session , we will proceed with transformation. Image Transformations like resizing, flipping, then Then we will perform some operations based on this masking.

Motion history image opencv python

Session Image Color Channels Merging and Splitting And then we will proceed with Image Channels. Session 21 - OpenCV - Gray scale Histograms, Color Histograms And in the next session, we will deal with Histograms, which is the graphical representation of the intensity of light, or pixels in that image.

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Session OpenCV - Histogram Equalization Then we will make use of Histogram Equalization to equalize the image to remove the rough edges of the image to equalize the color, the contrast of the image using the histogram equalizer. Session 24 - OpenCV - Image Blurring, Image Threshold The we will proceed with effects like blurring, then we will do thresholding in which we will be converting the normal image into binary format, like either Black or White, stuff like that Session OpenCV - Image Gradient Detection And then we will proceed with Gradient Detection and Edge Detection, which is greatly in use in the Image processing technology world.

Session Face Detection using OpenCV And then we will proceed with some Artificial Intelligence based applications like Face Detection That is detecting the number of faces inside a large image. Session Face Recognition using Machine Learning Then Face Recognition in which, the computer program will recognize the image based on the pre-learned faces. Session Digital Makeup Using a Technique called Digital Makeup to the face image and make it look more pretty or scary.

Draw shapes like polygons, lines etc over the area of interest and fill it with colors. Save the image if you want to.

Session Face Distance Calculation Calculate the numerical value of face match. Use this value to make decision if the face matches or not and the extend of match obtained. Session Real Time Face Recognition using Machine Learning Unlike the previous exercise in which the face recognition was done on a static image, here were are feeding the program with live videos from our computer's web camera. Session Optical Character Recognition - OCR using PyTesseract Library Then later on, we will go ahead with Optical Character Recognition, which is also an Artificial Intelligence based application Optical Character Recognition is an old Technology actually.

Session Simple Real-time motion detector using OpenCV from Camera Video Stream Session Object Recognition using pre-trained models Covering SSD, YOLO and Mask R-CNN Also real time object detection from webcam using SSD you may use the same technique for other models too Session Real-time Facial Expression Recognition System from Camera Video Stream So overall this is a complete package in which you can learn Computer Vision based Technology, Deep Learning based Face Detection,then Face Recognition and Optical Character Recognition.

Course Content. About the Instructor. Abhilash Nelson Courses People interested in this course also viewed. Frequently Asked Questions What is a Course? It is an online tutorial that covers a specific part of a topic in several sections. An Expert teaches the students with theoretical knowledge as well as with practical examples which makes it easy for students to understand.

How is a Course different from a Path and an E-Degree? The only prerequisite of this computer vision and deep learning crash course is that you know how to program.

OpenCV Complete Dummies Guide to Computer Vision with Python

We'll be using Python in the course, so if you have experience with Python, fantastic! And if not, don't worry, the language is easy to pick up and learn.

Computer Vision: Lego Blob Detection using OpenCV [Python]

Unfortunately, no. Prior programming experience is a requirement when taking this course. If you don't know how to program, you will need to learn how to code before joining this course.

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Absolutely not. I hate spam and I'm sure you do too. I will keep your email address safe and secure. If you have any other questions feel free to shoot me a message , and I will get back to you as soon as I can. Hey, I'm Adrian Rosebrock , a Ph. D and entrepreneur who has spent his entire adult life studying computer vision, machine learning, and deep learning.