k-l-lambda's picture
feat: add Python ML services (CPU mode) with model download
2b7aae2
import { Vector3 } from './Vector3.js';
import * as MathUtils from './MathUtils.js';
const _startP = /*@__PURE__*/ new Vector3();
const _startEnd = /*@__PURE__*/ new Vector3();
class Line3 {
constructor(start = new Vector3(), end = new Vector3()) {
this.start = start;
this.end = end;
}
set(start, end) {
this.start.copy(start);
this.end.copy(end);
return this;
}
copy(line) {
this.start.copy(line.start);
this.end.copy(line.end);
return this;
}
getCenter(target) {
return target.addVectors(this.start, this.end).multiplyScalar(0.5);
}
delta(target) {
return target.subVectors(this.end, this.start);
}
distanceSq() {
return this.start.distanceToSquared(this.end);
}
distance() {
return this.start.distanceTo(this.end);
}
at(t, target) {
return this.delta(target).multiplyScalar(t).add(this.start);
}
closestPointToPointParameter(point, clampToLine) {
_startP.subVectors(point, this.start);
_startEnd.subVectors(this.end, this.start);
const startEnd2 = _startEnd.dot(_startEnd);
const startEnd_startP = _startEnd.dot(_startP);
let t = startEnd_startP / startEnd2;
if (clampToLine) {
t = MathUtils.clamp(t, 0, 1);
}
return t;
}
closestPointToPoint(point, clampToLine, target) {
const t = this.closestPointToPointParameter(point, clampToLine);
return this.delta(target).multiplyScalar(t).add(this.start);
}
applyMatrix4(matrix) {
this.start.applyMatrix4(matrix);
this.end.applyMatrix4(matrix);
return this;
}
equals(line) {
return line.start.equals(this.start) && line.end.equals(this.end);
}
clone() {
return new this.constructor().copy(this);
}
}
export { Line3 };