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A python based NFT generator which programatically generates unique images using weighted layer files


nft-generator-py is a python based NFT generator which programatically generates unique images using weighted layer files. The program is simple to use, and new layers can be added by adding a new layer object and adding names, weights, and image files to the object. You can View The Demo here.

How it works

  • A call to generate_unique_images(amount, config) is made, which is the meat of the application where all the processing happens.
  • The config object is read and for each object in the layers list, random values are selected and checked for uniqueness against all previously generated metadata files.
  • Once we have amount unique tokens created, we layer them against eachother and output them and their metadata to their respective folders, ./metadata and ./images.

Configuration

{
  "layers": [
    {
      "name": "Background",
      "values": ["Blue", "Orange", "Purple", "Red", "Yellow"],
      "trait_path": "./trait-layers/backgrounds",
      "filename": ["blue", "orange", "purple", "red", "yellow"],
      "weights": [30, 45, 15, 5, 10]
    },
    ...
  ],
  "name": "NFT #"
}

The config object is a dict that contains layers and name objects that can be changed to produce different outputs when running the program. Within metadata files, tokens are named using the configuration’s name parameter.

  • In ascending order, tokenIds are appended to the name resulting in NFT metadata names such as NFT #0001.
  • tokenIds are padded to the largest amount generated. IE, generating 999 objects will result in names NFT #001, using the above configuration, and generating 1000 objects will result in NFT #0001.

The layers list contains layer objects that define the layers for the program to use when generating unique tokens. Each layer has a name, which will be displayed as an attribute, values, trait_path, filename, and weights.

  • trait_path refers to the path where the image files in filename can be found. Please note that filenames omit .png, and it will automatically be prepended.

  • weight corresponds with the percent chance that the specific value that weight corresponds to will be selected when the program is run. The weights must add up to 100, or the program will fail.

Troubleshooting

  • All images should be in .png format.
  • All images should be the same size in pixels, IE: 1000×1000.
  • The weight values for each attribute should add up to equal 100.

Credits

This project is completely coded by Jonathan Becker, using no external libraries.

GitHub

GitHub – Jon-Becker/nft-generator-py: Unique image & metadata generation using weighted layer collections.

Unique image & metadata generation using weighted layer collections. – GitHub – Jon-Becker/nft-generator-py: Unique image & metadata generation using weighted layer collections.


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