nft-generator-py

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.

Usage

As of v2.0.0, nft-generator-py will use the argparse library in order to support external configuration files and won't require users to interact with the python files themselves.

Install requirements: python3 -m pip install -r requirements.txt
Make a configuration JSON file. See the configuration section below for specifications.
Add layer files into the /images folder.
Run the command python3 generate.py --amount AMOUNT --config CONFIG

where:
1. AMOUNT is the amount of images to generate
2. CONFIG is the path pointing to a .json file containing valid program configuration.

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]
    },
    ...
  ],
  "incompatibilities": [
    {
      "layer": "Background",
      "value": "Blue",
      "incompatible_with": ["Python Logo 2"],
      "default": {
        "value": "Default Incompatibility",
        "filename": "./trait-layers/foreground/logo"
      }
    }
  ],
  "baseURI": ".",
  "name": "NFT #",
  "description": "This is a description for this NFT series."
}

The config object is a dict that contains configuration instructions that can be changed to produce different outputs when running the program. Within metadata files, tokens are named using the configuration's name parameter, and described using the description 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.
As of v1.0.2, padding filenames has been removed.

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.

The incompatibilities list contains an object that tells the program what layers are incompatible with what. In the above configuration, A Blue Background layer will never be generated with Python Logo 2.

layer refers to the targeted layer.
value is the value of the layer that is incompatible with attributes within the incompatible_with list.
incompatible_with is the list of incompatible layers that will never be selected when layer has attribute value.
An optional default object can be provided to each incompatibility. This object will be selected 100% of the time if present and an incompatible layer is selected. The default object has a value and filename attribute.
- value is the name of the default selection which will be displayed in the metadata.
- filename is the path to the image file that will be used as the default selection.

As of v1.0.2, the IPFS CID may be updated programatically after generating NFTs and uploading /images to IPFS. This will update all metadata files to correctly point "image" to the IPFS CID.

This is an optional step, and can be exited safely using enter or control + c.

Troubleshooting

All images should be in .png format.
All images should be the same size in pixels, IE: 1000x1000.
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.

Visual917 / nft-generator-py