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https://github.com/l3str4nge/imgprocalgs

Image processing algorithms implementation in pure Python :wrench:
https://github.com/l3str4nge/imgprocalgs

algorithms contributions-welcome flask good-first-issue imageprocessing python

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Image processing algorithms implementation in pure Python :wrench:

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ImageProcessingAlgorithms











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))

##### Installation
```buildoutcfg
git clone https://github.com/mateuszz0000/imgprocalgs
pip install -U imgprocalgs/
```

##### Usage
Different entry point is prepared for each type of algorithm:
```buildoutcfg
imgprocalgs-sepia
imgprocalgs-tiltshift
imgprocalgs-dithering
imgprocalgs-negative
imgprocalgs-color-accent
```
##### Example

#### Contribution
Read our [Contribution Guidelines](CONTRIBUTING.md) before you contribute.