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Certified Computer Vision Expert (2025)
Rating: 4.4 out of 5(9 ratings)
215 students

Certified Computer Vision Expert (2025)

Master OpenCV and MediaPipe: Learn Image Processing, Object Detection, Gesture Control, and Real-time Applications.
Created byKalyanasundaram K
Last updated 1/2025
English

What you'll learn

  • Gain hands-on experience with OpenCV to process and manipulate images and videos.
  • Master real-time applications such as hand tracking, pose estimation, and gesture recognition with MediaPipe.
  • Learn advanced techniques like feature detection, object recognition, and image segmentation.
  • Build and deploy machine learning models for computer vision tasks like object detection and face recognition.

Course content

4 sections • 30 lectures • 2h 13m total length

  • Day 1: Introduction9:25
  • Day 2: Image Basics5:40

    Learn to convert an image to grayscale, HSV, and LAB color spaces and display the original alongside each result in four tabs using OpenCV.

  • Day 3: Basic Image Operations6:43
  • Day 4: Drawing and Editing8:37

    Draw shapes on images using OpenCV and numpy to create a canvas, then render lines, rectangles, circles, and text with cv2, and display the result with cv2.imshow.

  • Day 5: Video Processing Basics4:17
  • Day 6: Image Thresholding5:16
  • Day 7: Recap and Mini-Project2:13

    Create a photo collage from six to eight images, view the combined output, save it as day seven, and upload your collage to the Udemy resources link.

Requirements

  • Basic knowledge of Python programming. Familiarity with computer science and programming fundamentals. No prior experience in computer vision is required.

Description

This comprehensive course is designed to guide you through the essentials and advanced concepts of computer vision using OpenCV and MediaPipe. You will start by understanding the basics of image processing, including loading, displaying, and saving images. As you progress, you'll dive into intermediate topics like image filtering, edge detection, and contour analysis. The course also covers advanced applications such as pose estimation, hand tracking, and facial recognition with MediaPipe.

Throughout the course, you will work on practical projects, such as building a document scanner, creating a real-time gesture-controlled media player, and applying machine learning models for object detection and face recognition. By the end of the course, you'll be equipped to integrate OpenCV and MediaPipe in your projects, design custom computer vision applications, and deploy real-time systems for various industries.

The course includes hands-on exercises, mini-projects, and a capstone project that helps solidify your learning. Whether you're an aspiring computer vision developer or an AI enthusiast, this course provides the skills necessary to tackle real-world computer vision problems and enhance your career.
Master OpenCV and MediaPipe: Learn Image Processing, Object Detection, Gesture Control, and Real-time Applications.

"Join 'Master OpenCV & MediaPipe' to learn image processing, object detection, and real-time apps!"

Who this course is for:

  • Aspiring computer vision developers, AI enthusiasts, and Python programmers. Students or professionals seeking to enhance their skills in computer vision, image processing, and machine learning. Anyone interested in building real-time applications using OpenCV and MediaPipe.

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