Computer Vision with Python and OpenCV

Take our Computer Vision course to learn OpenCV! In this course, you’ll use the OpenCV Python library to process and analyze images and video data.

 

 

Student rating

5.00 Out Of 45 Students

What You’ll Learn

  • Understand basics of NumPy
  • Manipulate and open Images with NumPy
  • Use OpenCV to work with image files
  • Use Python and OpenCV to draw shapes on images and videos
  • Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
  • Create Color Histograms with OpenCV
  • Open and Stream video with Python and OpenCV
  • Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python
  • Create Face Detection Software
  • Segment Images with the Watershed Algorithm
  • Track Objects in Video
  • Use Python and Deep Learning to build image classifiers
  • Work with Tensorflow, Keras, and Python to train on your own custom images.

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Course Content

This course covers everything you need to know to become an expert in computer vision! You’ll start the course by learning about numerical processing and image manipulation with the NumPy library. The course will teach you how to use the OpenCV library to open and work with image basics to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more. After covering images, you’ll learn video basics with OpenCV, including working with streaming video, optical flow and object detection, including face detection and object tracking. The latest and more advanced deep learning topics will be covered as well including image recognition, custom image classifications, and the YOLO (you only look once) deep learning network.

 

 

  • Numpy
  • Image Handling with Python & OpenCV
    • Image I/O
    • Thresholding
    • Filtering
    • Histograms
    • Template Matching
    • Gradient based Methods
    • Edge Detection
    • Object Detection
    • Facial Recognition (you cover face detection, but expansion to facial recognition is trivial with dlib – Lets discuss!)
  • Video Handling with Python & OpenCV
    • Video & Webcam I/O
    • Optical Flow
    • Tracking
  • Deep Learning

 

 

Intermediate to experienced Python developers seeking to use Python for image and video data with a focus on the OpenCV library

 

 

Course Description

OpenCV, once released by INTEL to benchmark their processors, comes with a huge array of functionality, even deep learning-based, and allows for efficient image processing and computer vision. Tracking, Object Detection, Facial Recognition, and much more – all in one library. Understanding how to work with image and video data is becoming vital in modern applications. 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!

 

 

What Students Are Saying

This course was really fabulous starting from basics of image processing to advanced computer vision tools like object detection, object tracking as well as deep learning required for computer vision. I enjoyed this course alot and have learnt so many things.

Nishant Wadhwani

This is a very beginner-friendly course. I'm liking it.

Bobur Shakirov

So far so good. concept along with code, that is how i like it

Henok Mengistu

You are Amazing Jose. You are the reason me and my buddy Picked this course. My other buddy picked up a Python Bootcamp Course and He suggested me to take this one with utmost Confidence. Your course is the best for anyone to get started in OpenCV and Deep Learning

Shubham Pawar

This is an excellent course designed for OpenCV covering all the major aspects of Image and Video Processing. A lot of details of Python programming are provided by using real time coding examples. Deep Learning modules come as an added advantage with this course. Fundamental techniques and datasets are used very well with explanatory examples. I highly appreciate this course and personally thanks Jose Portilla for his sincere efforts.

Pragyesh Kumar

the delivery in this course is one of the best have seen so far, the use of the assessment is really nice this helps reinforce what you have learnt in any section, would encourage everyone not to skip the assessment. after going through this course I had to buy another course from jose

Jonah Sokipriala

It is the second time when Jose is teaching me something in python nso far I feel that Jose is the best suitable instructor for me

Tanush Gupta

My only issue is that the course relies on installing Anaconda python environment. I'd prefer to work with Pyenv and venv to install packages in order to keep my many different environments (one for each class I am taking) separate and organized. So I am having to hack my way around this limitation.

Matt Kennedy

The course is completely understandable and very interesting, as far as I know, this is the best course on OpenCV for python

Stanislav Lazarenko

Course is very interesting and even the explanation is on point.

Urvi Agrawal
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Course type
  • In-House
  • Self-Paced
Student rating

5.00

Course length

92 Lectures

22 Hours

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