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https://github.com/setanarut/halftonism

Artistic halftone generation library
https://github.com/setanarut/halftonism

animated-gif art artistic artistic-coding color-cycle color-cycling computer-graphics digital-elevation-model fractal gif-animation gif-creator halftone halftoning loop optical-illusion procedural-art

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Artistic halftone generation library

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README 

        
# Halftonism



Artistic halftone generation library



![example_6_tri_fs2_m70](./assets/eyeswide.gif)



## Installation



```shell

pip install git+https://github.com/setanarut/halftonism

```



## Tutorial



```python

from halftonism import Project



p = Project("example.ora", repeat=16, waveform="triangle")

p.save_GIF("example.gif", scale=0.25, miliseconds=70, colors=30, resample=3)

```



![Krita ORA Screenshot](./example/example.gif)



### Preparing the ORA file



![Krita ORA Screenshot](./assets/krita_ORA_SS.jpg)



You can open the example.ora file in [example](./example/) folder with the [Krita](https://docs.krita.org/en/general_concepts/file_formats/file_ora.html). ([Openraster](https://www.openraster.org/) format). In the example you can see the color layers obtained using [fastLayerDecomposition](https://github.com/CraGL/fastLayerDecomposition) repository. After installing the halftonism package, the `folder2ora` command line tool is installed. Using this, you can convert the folder full of PNG layers obtained with [fastLayerDecomposition](https://github.com/CraGL/fastLayerDecomposition) into an ORA file. Saves it with the name `output.ora`.



```bash

$ folder2ora ~/Downloads/layers_folder



# saved -> ~/Downloads/layers_folder/output.ora

```



Alternatively you can decompose and save image as an ORA file with the [decompose](https://github.com/setanarut/decompose) package. [decompose](https://github.com/setanarut/decompose) package separates very quickly using pytorch but the colors are  inaccurate a little bit depending on the palette. 



```bash

$ decomp ~/Desktop/img.png

# Decomposer mask generation...

# Decomposer processing alpha layers...

# Decomposer Done!

# ORA saved: img.ora

# 7

# Palette saved: img_palette.png

```



Also you can paint it by hand without layer decompositing. Play around with layer orders and alpha levels for a more color balanced halftone outputs.  



#### ORA Layer Structure



Before processing the ORA file with Python, you have to follow the template below.



1. Each color layer should contain only a single color.



2. The bottom background layer (base color) must be solid color.



3. There should be a grayscale fractal heightmap at the top layer for halftone patterns. Top layer can be a computer generated heightmaps or [real DEM images](https://tangrams.github.io/heightmapper/) or any suitable grayscale gradient.



#### Some procedural techniques.



- Procedural terrains based on simplified landscape evolution model (LEM) [github.com/TadaTeruki/fastlem-random-terrain](https://github.com/TadaTeruki/fastlem-random-terrain)

- Diffusion-limited aggregation

- Mandelbrot Fractals

- Hydraulic erosion simulation across a heightfield (Noise)



##### Fastlem terrain fractal example



![fastlem](./assets/fastlem.gif)



##### Mandelbrot fractal example



![mandel](./assets/mandel.gif)



### ORA processing with halftonism package



Halftone animation is created with 256 pixels linear grayscale gradient [cycling](https://en.wikipedia.org/wiki/Color_cycling), also known as palette shifting or palette animation. The halftone pattern and color layer are mixed with the [*Hard Mix*]([https://](http://www.simplefilter.de/en/basics/mixmods.html)) blending mode (mix *halftone gradient pattern* and *color layer* by 50%. If the alpha value is greater than 128, set the color to 255, otherwise set the color to 0).  



#### `Project()` parameters



##### waveform



Waveform of gradient. `Project()` has parameters `waveform="sawtooth"`, `waveform="triangle"` and `waveform="sine"`. The effects are shown below, respectively.



![downsample](./assets/waveforms.png)



##### repeat



This number determines how many times gradient will be divided. The formula` (256 / repeat) / frame_skipping` gives the number of animation frames. (frame_skipping is 1 by default, meaning it is disabled). For example, `repeat=8` will give 32 frames. (**256/8/1 = 32 frames**).



Let's save all sawtooth gradient repetitions from 1 to 16 as image. It will help to understand. Height increased from 256x1 to 256x32 and image rotated 90 degree for visibility.



```python

from PIL import Image

import numpy as np

from halftonism.utils import gradient_vstack, gradient



stack = gradient_vstack(gradient(1, "sawtooth"), 32)

for repeat in range(2, 17):

    stack = np.vstack((stack, gradient_vstack(gradient(repeat, "sawtooth"), 32)))

im = Image.fromarray(stack)

im.rotate(90, expand=True).save("gradient_repeats.png")



```



![Gradient repeats 1-16 ](./assets/gradient_repeats.png)



##### frame_skipping



You can skip frames to reduce GIF/APNG file size. This also reduces the frame jump effect in repeat numbers where the number 256 is not divisible, such as 3,7,10.



#### Antialiasing



For antialiasing, you can downscale image with [bicubic sampling](https://pillow.readthedocs.io/en/stable/handbook/concepts.html#PIL.Image.Resampling.BICUBIC). For example, you can start with 2000x2000 and downscale to 500x500 for final output (500 / 2000 = 0.25 scale). The `save_GIF()` `save_APNG()` and `save_frame()` methods have `scale` and [resample](https://pillow.readthedocs.io/en/stable/handbook/concepts.html#PIL.Image.Resampling.BICUBIC) arguments. 



Resampling example with `NEAREST` on the left and `BICUBIC` on the right. (scale 0.25)



![downsample](./assets/downsample.png)



```python

p.save_GIF("output.gif", scale=0.25, resample=Image.BICUBIC)

p.save_frame(0, "01_frame.png", scale=0.25., resample=3)

```