Are you interested in learning computer vision and image processing from scratch? Look no further than the course, Learn Computer Vision with OpenCV and Python. This course offers a comprehensive introduction to computer vision and image processing, covering everything from the basics to special applications like facial landmark detection and deep learning. With a 4.45 rating aggregate and 130 reviews, this course is a top-notch resource for anyone interested in computer vision.
Course Overview
The course covers all the key concepts of computer vision and OpenCV, starting with basic operations like histogram equalization and thresholding. From there, the course delves into more advanced topics like object detection, tracking, and deep learning. Throughout the course, you'll have access to real-world examples that demonstrate how these concepts are applied in practice. And with the addition of new special applications on a regular basis, you'll stay up-to-date with the latest developments in computer vision.
Why Choose This Course?
One of the main advantages of this course is its clear, easy-to-understand explanations. Unlike other resources that rely on heavily mathematical theory, this course focuses on implementation, allowing you to dive right in and start learning. The course also makes use of OpenCV, an open-source computer vision library that's widely used and supported, and Python, which allows you to focus on the problem without getting bogged down in programming syntax.
Furthermore, the course offers many special examples to help you understand the fundamental topics. You'll learn about keypoint matching, image segmentation, and object tracking, among other topics. And with new special applications added regularly, you'll have access to the latest tools and techniques in computer vision.
What You'll Learn
The course covers a wide range of topics, including:
- The key concepts of computer vision & OpenCV
- Basic operations: histogram equalization, thresholding, convolution, edge detection, sharpening, morphological operations, image pyramids
- Keypoints and keypoint matching
- Special App: mini-game using key points
- Image segmentation: segmentation and contours, contour properties, line detection, circle detection, blob detection, watershed segmentation
- Special App: people counter
- Object tracking: Tracking APIs, filtering by color
- Special App: tracking of moving object
- Object detection: haarcascade face and eye detection, HOG pedestrian detection
- Object detection with deep learning (including how to prepare and train your own deep learning model)
- Extra Chapter: facial landmarks and special applications (such as real time sleep and smile detection)
- Extra Chapter: different special applications (will be updated with special examples in different topics)
Student Reviews
Students rave about this course's clear explanations and breadth of material. One student notes, "This course offers an excellent introduction to computer vision. I appreciate that the explanations were easy to understand, and the examples were very helpful." Another student adds, "I really enjoyed the course and learned a lot. It's great that the course covers both the basics and special applications in such detail."
This course is ideal for anyone interested in computer vision and image processing, whether you're a beginner or have some prior experience. With its clear explanations, real-world examples, and constant updates, Learn Computer Vision with OpenCV and Python is an invaluable resource for anyone looking to master this fascinating field.
