Computer Vision Masterclass

Learn in practice everything you need to know about Computer Vision! Build projects step by step using Python!

4.53 (1232 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Understand the basic intuition about Cascade and HOG classifiers to detect faces

Implement face detection using OpenCV and Dlib library

Learn how to detect other objects using OpenCV, such as cars, clocks, eyes, and full body of people

Compare the results of three face detectors: Haarcascade, HOG (Histogram of Oriented Gradients) and CNN (Convolutional Neural Networks)

Detect faces using images and the webcam

Understand the basic intuition about LBPH algorithm to recognize faces

Implement face recognition using OpenCV and Dlib library

Recognize faces using images and the webcam

Understand the basic intuition about KCF and CSRT algorithms to perform object tracking

Learn how to track objects in videos using OpenCV library

Learn everything you need to know about the theory behind neural networks, such as: perceptron, activation functions, weight update, backpropagation, gradient descent and a lot more

Implement dense neural networks to classify images

Learn how to extract pixels and features from images in order to build neural networks

Learn the theory behind convolutional neural networks and implement them using Python and TensorFlow

Implement transfer learning and fine tuning to get incredible results when classifying images

Use convolutional neural networks to classify the following emotions in images and videos: happy, anger, disgust, fear, surprise and neutral

Compress images using linear and convolutional autoencoders

Detect objects in images in videos using YOLO, one of the most powerful algorithms today

Recognize gestures and actions in videos using OpenCV

Learn how to create hallucinogenic images with Deep Dream

Learn how to revive famous artists with style transfer

Create images that don't exist in the real world with GANs (Generative Adversarial Networks)

Implement image segmentation do extract useful information from images and videos

Course Gallery

Computer Vision Masterclass – Screenshot 1 — Screenshot 1 – Computer Vision Masterclass

Computer Vision Masterclass – Screenshot 2 — Screenshot 2 – Computer Vision Masterclass

Computer Vision Masterclass – Screenshot 3 — Screenshot 3 – Computer Vision Masterclass

Computer Vision Masterclass – Screenshot 4 — Screenshot 4 – Computer Vision Masterclass

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Comidoc Review

Our Verdict

The Computer Vision Masterclass is a great starting point for beginners looking to dive into computer vision. Its strength lies in its practical, project-based approach that covers the basics of image processing and dives deep into neural networks. However, it may not provide enough challenge for seasoned programmers while those seeking detailed theoretical explanations might be left wanting more. Despite the occasional issues with pronunciation, this Masterclass is a great place to start your computer vision journey.

What We Liked

Comprehensive introduction to Computer Vision
Excellent coverage of neural networks and convolutional neural networks
Hands-on projects with clear explanations
Comprehensive face detection and recognition section

Potential Drawbacks

Relies heavily on libraries instead of implementing concepts from scratch
Could benefit from more theoretical detail
Later sections may feel less challenging for experienced programmers
Accent can sometimes make understanding difficult