Collection of common image processing algorithms. This project aims to learn digital image processing algorithms by coding them from scratch in Python >= 3.6. Small Flask application is used to generate output in website to see algorithm result.

Travis-CI is used for CI/CD environment.

Implemented so far:

• resizing algorithms:
  • Nearest neighbour (https://en.wikipedia.org/wiki/Nearest_neighbour_algorithm)
  • Bilinear interpolation (https://en.wikipedia.org/wiki/Bilinear_interpolation)
  • Bicubic interpolation (https://en.wikipedia.org/wiki/Bicubic_interpolation)
• other:
  • negative (https://en.wikipedia.org/wiki/Negative_(photography))
  • Tilt-shift (https://pl.wikipedia.org/wiki/Tilt-shift)
  • RGB to HSV conversion(https://en.wikipedia.org/wiki/HSL_and_HSV)
  • HSV to RGB conversion(https://en.wikipedia.org/wiki/HSL_and_HSV)
  • color accent
• tone
  • sepia (https://en.wikipedia.org/wiki/Photographic_print_toning#Sepia_toning)
• dithering
  • Floyd-Steinberg (https://en.wikipedia.org/wiki/Floyd%E2%80%93Steinberg_dithering)
  • Jarvis Judice Ninke (https://en.wikipedia.org/wiki/Dither)
  • Stucki (https://en.wikipedia.org/wiki/Dither)
• Convolution
  • Edge detection (https://en.wikipedia.org/wiki/Kernel_(image_processing))

git clone https://github.com/mateuszz0000/imgprocalgs
pip install -U imgprocalgs/

Different entry point is prepared for each type of algorithm:

imgprocalgs-sepia <OPTIONS>
imgprocalgs-tiltshift <OPTIONS>
imgprocalgs-dithering <OPTIONS>
imgprocalgs-negative <OPTIONS>
imgprocalgs-color-accent <OPTIONS>

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