Are you interested in mastering Computer Vision using OpenCV4 in Python? Look no further than the comprehensive course, "Master Computer Vision™ OpenCV4 in Python with Deep Learning". With over 20 years of experience, this course review content writer can attest that this is one of the most thorough and well-taught courses on OpenCV available on the web.
Why Choose This Course?
Firstly, it offers incredible value with over 50 code examples and 21 awesome projects to work on. Secondly, it covers the most up to date methods and technologies in computer vision, including Deep Learning with Keras and TensorFlow.
What's more, the demand for computer vision expertise is skyrocketing, with apps and industries making amazing use of the technology, from billion-dollar apps such as Pokémon GO, Snapchat, and up and coming apps like MSQRD and PRISMA, to tech giants like Facebook, Google, Microsoft, Apple, Amazon, and Tesla. The opportunities in this field are endless and incredibly lucrative, with high paying Computer Vision Engineer roles going for $400-$1000 USD/Day.
Course Contents
The course comprises of 90 lectures and over 20 hours of content, covering all key concepts of Computer Vision, OpenCV, and Deep Learning in a no-nonsense practical way, making it easy to understand. You'll get to learn and work on various projects, including:
- Live Drawing Sketch using your webcam
- Identifying Shapes
- Counting Circles and Ellipses
- Finding Waldo
- Object Detection for faces, people & cars.
- Car and Pedestrian Detector using Cascade Classifiers
- Live Face Swapper (like MSQRD & Snapchat filters!!)
- Facial Recognition
- Ball Tracking
- Photo-Restoration
- Automatic Number-Plate Recognition (ALPR)
- Multi-Object Detection in OpenCV (up to 90 Objects!) using SSD (Single Shot Detector)
- Colorize Black & White Photos and Video using Caffe
- Handwritten Digit Classification
- Facial Landmark Detection and Analysis
- Motion Analysis and Object Tracking
- Extract and Classify Credit Card Numbers
- Deep Learning with Keras (3+ hours) including creating Handwritten Digit Classifiers, Multi-Image Classifiers, and Cats vs Dogs Classifier, and boosting CNN performance using data augmentation
- Computational Photography Techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old, damaged photos)
- Neural Style Transfer Mini-Project
Notably, all tutorials will provide the practical application of CV concepts, allowing students to understand better and enhance their skills.
Course Curriculum
Unlock the power of OpenCV with comprehensive theory, tips, code, and projects in the course. Here is what you'll learn:
Section 1:
- Course Overview
- Computer Vision - Understanding the Basics
- What is OpenCV
- Setup for Windows
- Setup for Mac
- Setup for Ubuntu
Section 2:
- Image Manipulations with OpenCV(Theory)
- Handling Images with OpenCV
- Image Manipulations with OpenCV (Practice)
- Color Maps and Color Spaces
- Blurring and Smoothing
- Thresholding and Binarization
- Gradients and Edge Detection
- Canny Edge Detector
Section 3:
- Image Geometry(Theory)
- Image Translation
- Rotation, Resizing, and Flipping
- Cropping Image
- Arithmetic Operations
- Image Pyramids
- Contours (Theory)
- Contour Detection
- Contour Properties
- Approximating Contours
- Matching Contour Shapes
- Line Detection
- Circle Detection
Course Review
Currently, the course has an aggregate rating of 4.23 out of 5 from 3608 course reviews. Many of the earlier poor reviews were during a period when the course material was outdated, and many of the example codes were broken. Nevertheless, these issues have been fixed since early 2019.
Reviews from our students have been remarkable, with many praising the course for its practical and concise delivery of key Computer Vision concepts and comprehensive projects that help students enhance their skills, fully equipping them for a successful career in Computer Vision Engineering.
One student was so impressed by the course that they said: "I'm amazed at the possibilities. Very educational, learning more than I ever thought was possible. Now, being able to actually use it for a practical purpose is intriguing. There's much more to learn and apply", while another stated, "I am extremely impressed by this course!! I think this is by far the best Computer Vision course on Udemy. This 6.5-hour course blows away my college class by miles!!"
Enroll Now
In sum, if you're interested in mastering Computer Vision using OpenCV4 in Python, this course is for you! With easy-to-understand explanations, practical and comprehensive projects to work on, and 3+ hours of Deep Learning with Keras, this course offers incredible value. What's more, with our continuous updates, fixes, and new amazing projects every month, you'll never be on your own!
Enroll now and start the process of becoming a master in Computer Vision today!
