Generate your collection

Create generative NFTs collection

First of all download the generator below:

https://github.com/AlphagaMarket/nft-generator/archive/refs/heads/main.zip

Create generative nft by using the canvas api and node js. Before you use the generation engine, make sure you have node.js(v14.0.0) installed. NodeJS : https://nodejs.org/

Installation 🛠️

Go to the root of your folder and run this command if you have yarn installed.

yarn install

Alternatively you can run this command if you have node installed.

npm install

Usage

Create your different layers as folders in the layers directory, and add all the layer assets in these directories. You can name the assets anything as long as it has a rarity weight attached in the file name like so: example element#70.png. You can optionally change the delimiter # to anything you would like to use in the variable rarityDelimiter in the src/config.js file.

Once you have all your layers, go into src/config.js and update the layerConfigurations objects layersOrder array to be your layer folders name in order of the back layer to the front layer.

Example: If you were creating a portrait design, you might have a background, then a head, a mouth, eyes, eyewear, and then headwear, so your layersOrder would look something like this:

const layerConfigurations = [
  {
    growEditionSizeTo: 100,
    layersOrder: [
      { name: "Head" },
      { name: "Mouth" },
      { name: "Eyes" },
      { name: "Eyeswear" },
      { name: "Headwear" },
    ],
  },
];

The name of each layer object represents the name of the folder (in /layers/) that the images reside in.

Optionally you can now add multiple different layerConfigurations to your collection. Each configuration can be unique and have different layer orders, use the same layers or introduce new ones. This gives the artist flexibility when it comes to fine tuning their collections to their needs.

Example: If you were creating a portrait design, you might have a background, then a head, a mouth, eyes, eyewear, and then headwear and you want to create a new race or just simple re-order the layers or even introduce new layers, then you're layerConfigurations and layersOrder would look something like this:

const layerConfigurations = [
  {
    // Creates up to 50 nfts
    growEditionSizeTo: 50,
    layersOrder: [
      { name: "Background" },
      { name: "Head" },
      { name: "Mouth" },
      { name: "Eyes" },
      { name: "Eyeswear" },
      { name: "Headwear" },
    ],
  },
  {
    // Creates an additional 100 nfts
    growEditionSizeTo: 150,
    layersOrder: [
      { name: "Background" },
      { name: "Head" },
      { name: "Eyes" },
      { name: "Mouth" },
      { name: "Eyeswear" },
      { name: "Headwear" },
      { name: "AlienHeadwear" },
    ],
  },
];

Update your format size, ie the outputted image size, and the growEditionSizeTo on each layerConfigurations object, which is the amount of variation outputted.

You can mix up the layerConfigurations order on how the images are saved by setting the variable shuffleLayerConfigurations in the config.js file to true. It is false by default and will save all images in numerical order.

If you want to have logs to debug and see what is happening when you generate images you can set the variable debugLogs in the config.js file to true. It is false by default, so you will only see general logs.

If you want to play around with different blending modes, you can add a blend: MODE.colorBurn field to the layersOrder options object.

If you need a layers to have a different opacity then you can add the opacity: 0.7 field to the layersOrder options object as well.

If you want to have a layer ignored in the DNA uniqueness check, you can set bypassDNA: true in the options object. This has the effect of making sure the rest of the traits are unique while not considering the Background Layers as traits, for example. The layers are included in the final image.

To use a different metadata attribute name you can add the displayName: "Awesome Eye Color" to the options object. All options are optional and can be addes on the same layer if you want to.

Here is an example on how you can play around with both filter fields:

const layerConfigurations = [
  {
    growEditionSizeTo: 5,
    layersOrder: [
      { name: "Eyeball" },
      {
        name: "Eye color",
        options: {
          blend: MODE.destinationIn,
          opacity: 0.2,
          displayName: "Awesome Eye Color",
        },
      },
      { name: "Iris" },
      { name: "Shine" },
      { name: "Bottom lid", options: { blend: MODE.overlay, opacity: 0.7 } },
      { name: "Top lid" },
    ],
  },
];

Here is a list of the different blending modes that you can optionally use.

const MODE = {
  sourceOver: "source-over",
  sourceIn: "source-in",
  sourceOut: "source-out",
  sourceAtop: "source-out",
  destinationOver: "destination-over",
  destinationIn: "destination-in",
  destinationOut: "destination-out",
  destinationAtop: "destination-atop",
  lighter: "lighter",
  copy: "copy",
  xor: "xor",
  multiply: "multiply",
  screen: "screen",
  overlay: "overlay",
  darken: "darken",
  lighten: "lighten",
  colorDodge: "color-dodge",
  colorBurn: "color-burn",
  hardLight: "hard-light",
  softLight: "soft-light",
  difference: "difference",
  exclusion: "exclusion",
  hue: "hue",
  saturation: "saturation",
  color: "color",
  luminosity: "luminosity",
};

When you are ready, run the following command and your outputted art will be in the build/images directory and the json in the build/json directory:

npm run build

or

node index.js

The program will output all the images in the build/images directory along with the metadata files in the build/json directory. Each collection will have a _metadata.json file that consists of all the metadata in the collection inside the build/json directory. The build/json folder also will contain all the single json files that represent each image file. The single json file of a image will look something like this:

{
  "name": "#1",
  "description": "This is the description of your NFT project",
  "image": "https://arweave.net/your_data_tx_id/1.png",
  "attributes": [
    { "trait_type": "Background", "value": "Black" },
    { "trait_type": "Eyeball", "value": "Red" },
    { "trait_type": "Eye color", "value": "Yellow" },
    { "trait_type": "Iris", "value": "Small" },
    { "trait_type": "Shine", "value": "Shapes" },
    { "trait_type": "Bottom lid", "value": "Low" },
    { "trait_type": "Top lid", "value": "Middle" }
  ]
}

You can also add extra metadata to each metadata file by adding your extra items, (key: value) pairs to the extraMetadata object variable in the config.js file.

const extraMetadata = {
  creator: "Alphaga",
};

If you don't need extra metadata, simply leave the object empty. It is empty by default.

const extraMetadata = {};

That's it, you're done.

Utils

Updating baseUri for IPFS and description

You might possibly want to update the baseUri and description after you have ran your collection. To update the baseUri and description simply run:

npm run update_info

Generate a preview image

Create a preview image collage of your collection, run:

npm run preview

Generate GIF images from collection

In order to export gifs based on the layers created, you just need to set the export on the gif object in the src/config.js file to true. You can also play around with the repeat, quality and the delay of the exported gif.

Setting the repeat: -1 will produce a one time render and repeat: 0 will loop forever.

const gif = {
  export: true,
  repeat: 0,
  quality: 100,
  delay: 500,
};

Printing rarity data (Experimental feature)

To see the percentages of each attribute across your collection, run:

npm run rarity

The output will look something like this:

Trait type: Top lid
{
  trait: 'High',
  chance: '30',
  occurrence: '3 in 20 editions (15.00 %)'
}
{
  trait: 'Low',
  chance: '20',
  occurrence: '3 in 20 editions (15.00 %)'
}
{
  trait: 'Middle',
  chance: '50',
  occurrence: '14 in 20 editions (70.00 %)'
}

Hope you create some awesome NFTs Collections with this