starry / backend /libs /three /geometries /PlaneGeometry.js
k-l-lambda's picture
feat: add Python ML services (CPU mode) with model download
2b7aae2
import { BufferGeometry } from '../core/BufferGeometry.js';
import { Float32BufferAttribute } from '../core/BufferAttribute.js';
class PlaneGeometry extends BufferGeometry {
constructor(width = 1, height = 1, widthSegments = 1, heightSegments = 1) {
super();
this.type = 'PlaneGeometry';
this.parameters = {
width: width,
height: height,
widthSegments: widthSegments,
heightSegments: heightSegments,
};
const width_half = width / 2;
const height_half = height / 2;
const gridX = Math.floor(widthSegments);
const gridY = Math.floor(heightSegments);
const gridX1 = gridX + 1;
const gridY1 = gridY + 1;
const segment_width = width / gridX;
const segment_height = height / gridY;
//
const indices = [];
const vertices = [];
const normals = [];
const uvs = [];
for (let iy = 0; iy < gridY1; iy++) {
const y = iy * segment_height - height_half;
for (let ix = 0; ix < gridX1; ix++) {
const x = ix * segment_width - width_half;
vertices.push(x, -y, 0);
normals.push(0, 0, 1);
uvs.push(ix / gridX);
uvs.push(1 - iy / gridY);
}
}
for (let iy = 0; iy < gridY; iy++) {
for (let ix = 0; ix < gridX; ix++) {
const a = ix + gridX1 * iy;
const b = ix + gridX1 * (iy + 1);
const c = ix + 1 + gridX1 * (iy + 1);
const d = ix + 1 + gridX1 * iy;
indices.push(a, b, d);
indices.push(b, c, d);
}
}
this.setIndex(indices);
this.setAttribute('position', new Float32BufferAttribute(vertices, 3));
this.setAttribute('normal', new Float32BufferAttribute(normals, 3));
this.setAttribute('uv', new Float32BufferAttribute(uvs, 2));
}
static fromJSON(data) {
return new PlaneGeometry(data.width, data.height, data.widthSegments, data.heightSegments);
}
}
export { PlaneGeometry, PlaneGeometry as PlaneBufferGeometry };