init

index.ts

@@ -0,0 +1,52 @@
+import sharp, { type OverlayOptions } from 'sharp';
+import { LAYERS, weightedChoice } from './layers';
+
+const BASE_SHAPE_PATH = './assets/base_shape.png';
+
+export type Trait = 'skin' | 'nose' | 'eyes' | 'mouth' | 'detail';
+
+export type Layer = {
+    trait: Trait,
+    path: string,
+    chance?: number,
+    options: TraitOption[]
+};
+
+export type TraitOption = {
+    fileName: string,
+    weight?: number
+};
+
+async function generateRandomImage(fileName: string, orderedLayers: Layer[]) {
+    const layers: { input: string }[] = [];
+
+    for (const layer of orderedLayers) {
+        if (layer.chance && Math.random() > layer.chance) {
+            continue;
+        }
+
+        const choice = weightedChoice(layer.options);
+
+        layers.push({ input: `${layer.path}${choice}` });
+    }
+
+    const image = sharp(BASE_SHAPE_PATH).composite(layers);
+
+    await Bun.write(`./output/${fileName}`, await image.toBuffer());
+}
+
+for (let i = 0; i < 100; i++) {
+    await generateRandomImage(`characters/${i}.png`, LAYERS);
+}
+
+// combine into a single grid image
+const characters: OverlayOptions[] = [];
+for (let i = 0; i < 100; i++) {
+    characters.push({ input: `./output/characters/${i}.png`, left: (i % 10) * 16, top: Math.floor(i / 10.0) * 16 });
+}
+
+const grid = sharp({ create: { width: 160, height: 160, channels: 4, background: { r: 0, g: 0, b: 0, alpha: 0 } } }).composite(characters).png();
+
+await Bun.write('./output/grid.png', await grid.toBuffer());
+
+console.log('Finished generation');