Image Processing Masterclass with Python

Get the ultimate combination of skills with Python + Graphics & transform images like a pro with our Python Masterclass.

(IMAGE-PYTHON.AW1) / ISBN : 978-1-64459-649-4
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About This Course

Image Processing Masterclass with Python ~ Restore, Enlarge & Improve your image with smart functions & skills. 

Solve image processing issues, get Python at your fingertips & create a super-resolution image using SRGAN. Become the expert you look up to! 

Prepare with interactive training modules & courses that get you the best results

Skills You’ll Get

Learn Basic Image and Video Processing  Explore Image Manipulations With Different Python Libraries Remove objects with seam carving Use scikit-image and scipy.ndimage with warping/inverse warping Detect & Change Colors with OpenCV-Python Use Hashing to find similar images Image Super-Resolution with Deep Learning Model (SRGAN) Face morphing, swapping & parsing with scipy.spatial & OpenCV-python Face detection and recognition with Microsoft Cognitive Vision APIs Realistic Image Dehazing Using Deep Neural Net

1

Preface

2

Basic Image and Video Processing

  • Display RGB image color channels in 3D
  • Video I/O
  • Implement Instagram-like Gotham filter
  • Explore Image Manipulations With Different Python Libraries
  • Object removal with seam carving
  • Summary
  • Questions
  • References
3

More Image Transformation and Manipulation

  • Introduction
  • Applying Euclidean and Affine transformation on an image
  • Implement image transformation with warping/inverse warping using scikit-image and scipy.ndimage
  • Image projection with homography using scikit-image
  • Detecting Colors and Changing Colors of Objects with OpenCV-Python
  • Detecting Covid-19 Virus Objects with Colors in the HSV Colorspace
  • Finding duplicate and similar images with hashing
  • Summary
  • Questions
  • References
4

Sampling, Convolution, Discrete Fourier, Cosine and Wavelet Transform

  • Introduction
  • Fourier Transform Basics
  • Sampling to increase/decrease the resolution of an image
  • Denoising an image with LPF/Notch filter in the Frequency domain
  • Blurring an Image with an LPF in the Frequency Domain
  • Edge detection with high pass filters (HPF) in the frequency domain
  • Implementation of homomorphic filters
  • Summary
  • Questions
  • References
5

Discrete Cosine/Wavelet Transform and Deconvolution

  • Introduction
  • Template matching with phase-correlation in the frequency domain
  • Image compression with the Discrete Cosine Transform (DCT)
  • Image denoising with Discrete Cosine Transform (DCT)
  • Deconvolution for image deblurring
  • Image Denoising With Wavelets
  • Image fusion with wavelets
  • Secure spread spectrum digital watermarking with the DCT
  • Questions
  • References
6

Image Enhancement

  • Introduction
  • Image Enhancement Filters with PIL for noise removal and smoothing
  • Unsharp masking to sharpen an image
  • Averaging of images to remove random noise
  • Image denoising with curvature-driven algorithms
  • Contrast stretching/histogram equalization with opencv-python
  • Fingerprint cleaning and minutiaes extraction
  • Edge detection with LOG/zero-crossing, canny versus holistically-nested
  • Summary
  • Questions
  • References
7

More Image Enhancement

  • Object detection with Hough transform and colors
  • Object Saliency Map, Depth Map, And Tone Map (HDR) With OpenCV-python
  • Pyramid blending
  • Image Super Resolution with Deep Learning Model (SRGAN)
  • Low-Light Image Enhancement Using CNNs
  • Realistic Image Dehazing Using Deep Neural Net
  • Distributed image processing with Dask
  • Summary
  • Questions
  • References
8

Face Image Processing

  • Introduction
  • Face morphing with dlib, scipy.spatial, and opencv-python
  • Facial Landmark Detection with Deep Learning Models
  • Implementation of face swapping
  • Implementation of face parsing
  • Face recognition with FisherFaces
  • Face detection and recognition with Microsoft Cognitive Vision APIs
  • Summary
  • Questions
  • References

Any questions?
Check out the FAQs

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Yes, Python is a popular programming language. It can be utilized to process images. It is widely popular because - 

  • Tools are easy to use. 
  • Contains powerful libraries such as Pillow & OpenCV.

AI’s advent has increased the use of Image processing in various fields. This field is in demand & growing as one of the most preferred occupations by individuals.

  • OpenCV
  • SimpleCV
  • SimplelTK
  • Mahotas
  • Scikit-Image
  • Pillow

Yes, upon successful completion, you’ll receive a certificate to showcase your skills in Image Processing using Python.

Enhance & Resize any Image with Python

Make images look as good as real with Python. Start now!

$239.99

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