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Image Processing and Computer Vision with Python & OpenCV
Rating: 4.0 out of 5(120 ratings)
695 students

Image Processing and Computer Vision with Python & OpenCV

Learn Image Processing and Computer Vision from AI (ML & DL) professional
Last updated 8/2023
English

What you'll learn

  • Image Processing with Python (skimage) (90% hands on and 10% theory)
  • Image Processing and Computer Vision with OpenCV (90% hands on and 10% theory)
  • Morphological operations with OpenCV (90% hands on and 10% theory)
  • Face detection with OpenCV (90% hands on and 10% theory)
  • Feature detection with OpenCV (90% hands on and 10% theory)
  • Image matching with skimage (90% hands on and 10% theory)
  • Object detection with OpenCV (90% hands on and 10% theory)
  • Digit recognition with OpenCV (90% hands on and 10% theory)

Course content

12 sections77 lectures9h 20m total length
  • Introduction3:26
  • Installations7:16
  • Technologies5:44
  • Definition of image processing and Computer vision6:25
  • Explanation of Images attributes3:51
  • Color Spaces - BW vs Grey vs RGB8:47

Requirements

  • 1. Passion for Learning 2. Curiosity for image analysis 3. NumPy knowledge

Description

The Image Processing and Computer Vision world is too big to comprehend.  It has been backbone of many industry including Deep Learning. It is used across multiple places. As practitioner, I am trying to bring many relevant topics  under one umbrella in following topics.   

1. Image Processing with Python (skimage) (90% hands on and 10% theory)

2. Image Processing and Computer Vision with OpenCV (90% hands on and 10% theory)

3. Morphological operations with OpenCV (90% hands on and 10% theory)

4. Face detection with OpenCV (90% hands on and 10% theory)

5. Feature detection with OpenCV (90% hands on and 10% theory)

6. Image matching with skimage (90% hands on and 10% theory)

7. Object detection with OpenCV (90% hands on and 10% theory)

8. Digit recognition with OpenCV (90% hands on and 10% theory)

9. Autonomous vechile detection and movement. (90% hands on and 10% theory)

10. Deep learning concepts useful for Image Processing and Computer Vision. (90% hands on and 10% theory)

11. Python practice from Data Science point of view. (90% hands on and 10% theory)

12. The assignment will make you hands-on in Image Processing and Computer Vision.

13. ML practice useful for Image Processing and Computer Vision. (90% hands on and 10% theory)

14. Many other useful topics in Image Processing and Computer Vision. (90% hands on and 10% theory)

Who this course is for:

  • Any one eager to know about Image Processing and Computer Vision