v1.0.0

Genimate: A tool to create Generative Animations

This script can be used to assemble generative animated images using weighted components, and create the metadata in the format required by MintGarden.io's MintGarden Studio bulk minter. It makes use of Gifski an amazing lossless GIF creation tool.

I've tried to make this as beginner friendly as possible.

This is an extension of my NFT-Assembler-for-MintGarden-Bulk example, With the main difference being that this is intended to produce animated images.

Disclaimer:

• I am not affiliated with MintGarden.io
• This software is provided as is, for example purposes.

Dependancies

• Python 3
• Pillow 9.x run: pip install Pillow

Running the Example

1. Clone the repository to your device, or download the folder and extract the contents.
2. Navigate to the directory in your CLI (or right-click + open terminal here in the folder on Windows)
3. Type/paste `Done!" when done

4. Check the newly created ./collection/ folder and contents that have been created. Remember to look at the metadata file.

In the name of all that is good, please don't try to turn these example images into NFT's.

Usage

1. Create your own component PNG frames and place them in ./components/TraitName/TraitVariation directory, and name them 1.png -> X.png in chronological order

For example: ./components/Feature/Blackhole/1.png

*Your components can use any dimensions, as long as they are all the same.*

2. Edit the genimate.py file, set your collection's name, description and the amount of images to generate, the FPS and Frames per Animation configs

# Change these
COLLECTION_NAME = "Super Duper Animated Example Collection"
COLLECTION_DESCRIPTION = "Super Duper Animated Example NFT's"
TOTAL_IMAGES = 100 # Number of random unique images you want to generate
FRAMES_PER_ANIMATION = 3 # The number of frames that have been created for each trait variant
FPS = 5 # The speed of the Animation, the lower = slower

3. Replace the component names with the names of your TraitName directories
4. Adjust corresponding weights accordingly (lower = rarer)

# The weightings for each trait drive the rarity and add up to 100%
traits = [
    Trait(
        "Background", # Parent Folder
        ["Pink", "Teal", "Lime", "Cream"], # Sub Folder
        [30, 20, 10, 40]),
    Trait(
        "Feature", 
        ["House", "Tree", "Sun", "Moon"], 
        [15, 35, 35, 15]),
    Trait(
        "Face", 
        ["Round", "Square", "Triangle"], 
        [30, 50, 20]),
    Trait(
        "Eyes", 
        ["Blue", "Red", "Brown"], 
        [30, 10, 60]),
    Trait(
        "Nose", 
        ["Pointy", "Rounded", "Dots"], 
        [30 , 30 , 40]),
    Trait(
        "Mouth", 
        ["Smile", "Grumpy", "Neutral", "Cute"], 
        [30, 30, 20, 20]),
]

• Run the program, and generate your Animated Images and Metadata
• Run the program again until your batch of NFT's is just right!

Testing

This is especially important if you have edited the code beyond what is presented in these instructions.

To double-check that every NFT has unique trait assignments in the metadata, run python duplicate_identifier.py

You should get 0 duplicates identified.

Problems or need help?

Feel free to create an issue ticket, i will try to address as soon as possible

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Want to toss some Mojo's or an NFT at the Andy?
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Check out my collection, Proof of Synth and Time on dexie.space or MintGarden