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LinkedIn Learning

Building Computer Vision Applications with Python

via LinkedIn Learning

Overview

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Get a deeper understanding of computer vision by creating your own image processing applications in Python.

Syllabus

Introduction
  • Computer vision under the hood
  • What you should know
  • Using the exercise files
1. Setting Up Your Environment
  • Installing Anaconda and OpenCV
  • Testing your environment
2. The Basics of Image Processing
  • Image representation
  • Color encoding
  • Image file management
  • Resolution
  • Rotations and flips
  • Challenge: Manipulate some pictures
  • Solution: Manipulate some pictures
3. From Color to Black and White
  • Average grayscale
  • Weighted grayscale
  • Converting grayscale to black and white
  • Adaptive thresholding
  • Challenge: Removing color
  • Solution: Removing color
4. Filters
  • Convolution filters
  • Average filters
  • Median filters
  • Gaussian filters
  • Edge detection filters
  • Challenge: Convolution filters
  • Solution: Convolution filters
5. Image Scaling
  • Image downscaling methods
  • Downscaling example
  • Image upscaling methods
  • Upscaling example
  • Challenge: Resize a picture
  • Solution: Resize a picture
6. Fun with Cuts
  • Image cuts
  • Stitching two images together
  • Cuts in panoramic photography
  • Challenge: Stitch two pictures together
  • Solution: Stitch two pictures together
7. Morphological Modifications
  • Why modify objects?
  • Erosion and dilation
  • Open and close
  • Challenge: Help a robot
  • Solution: Help a robot
Conclusion
  • Next steps

Taught by

Eduardo Corpeño

Reviews

4.7 rating at LinkedIn Learning based on 276 ratings

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