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Gimp script-fu Glow Art!

Gimp script-fu Glow Art!

"Glow Art!" Gimp Script Turns your photo into a masterpiece of an Epic Glow art.
The following requirements must be met:

Gimp 2.10
Download Gimp
2 layers must be present: "background" and "brush" layer
LayerFX for 2.8 (Python-Fu)
Please read the following Tutorial

1. Installation

unpack the archive
The .zip archive from GitHub is structured (folder hierarchy) as you find it in their local Gimp install directory.
Copy all files/ folders in this directory "C:\Program Files\GIMP 2\share\gimp\2.0" or use Gimp User Folder "C:\Users\Your User Name\.gimp-2.8\" (Gimp v2.10: "C:\Users\Your User Name\AppData\Roaming\GIMP\2.10")
Now start Gimp
for a quick start, you can use the template ""

2. Prepare the picture

open an image of your choice (RGB, RGBA) and name this layer "background"
good results I have conceded with image sizes of 2500px and higher (picture 1)
create a new layer above the "background" layer called "brush" (picture 2). With the "brush" layer selected, brush onto the areas of your photo that you want to apply the effect to.

Please pay attention to the correct spelling of all 2 layers "background" and "brush" (picture 2).

3. start Script

Calling the script

  • " / Script-Fu / Glow Art! Effect / Glow Art! ..."
    (picture 3)

  • picture 3
    picture 3

4. The script window

  • picture 4
    picture 4
    • Language:
      Choose the language under which Gimp runs (en, de).
    • Run Interactive Mode?
      (expert mode)
    • Undo Mode?
      depending on the computer performance. Tip: Save your picture before you run the script so you can revert your picture ("File / Revert")

Now you can run the script with "OK"

  • picture 5
    picture 5
  • In the script process, you will have to make 2 entries (picture 5).
    2 times you will be prompted entries for "Solid Noise ..."(picture 5) to make. Play with the settings.
    "Solid Noise ..." Filter is responsible for the dark cracks in the background of the picture.

Depending on the size of your image could take several minutes.
The script in action:
Download on GitHub

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