@polygonjs/polygonjs
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node-based WebGL 3D engine https://polygonjs.com
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text/typescript
import {Object3D, Vector4} from 'three';
import {Hands, Options, Results} from '@mediapipe/hands';
import {CoreComputerVisionHandAttribute} from './Common';
import {ParamConfig} from '../../../engine/nodes/utils/params/ParamsConfig';
import {Constructor} from '../../../types/GlobalTypes';
import {isBoolean, isNumber, isString} from '../../Type';
import {DEFAULT_POSITION} from './Data';
import {ComputerVisionValidSource} from '../Common';
import {coreObjectClassFactory} from '../../geometry/CoreObjectFactory';
interface HandTrackingObjectAttributes {
selfieMode: boolean;
maxNumHands: number;
modelComplexity: boolean;
minDetectionConfidence: number;
minTrackingConfidence: number;
}
const DEFAULT: HandTrackingObjectAttributes = {
selfieMode: false,
maxNumHands: 1,
modelComplexity: true,
minDetectionConfidence: 0.5,
minTrackingConfidence: 0.5,
};
export function CoreComputerVisionHandParamConfig<TBase extends Constructor>(Base: TBase) {
return class Mixin extends Base {
/** @param selfieMode */
selfieMode = ParamConfig.BOOLEAN(DEFAULT.selfieMode);
/** @param Maximum number of hands to detect */
maxNumHands = ParamConfig.INTEGER(DEFAULT.maxNumHands, {
range: [0, 2],
rangeLocked: [true, false],
});
/** @param Complexity of the hand landmark model: 0 or 1. Landmark accuracy as well as inference latency generally go up with the model complexity */
modelComplexity = ParamConfig.BOOLEAN(DEFAULT.modelComplexity);
/** @param Minimum confidence value ([0.0, 1.0]) from the hand detection model for the detection to be considered successful */
minDetectionConfidence = ParamConfig.FLOAT(DEFAULT.minDetectionConfidence, {
range: [0, 1],
rangeLocked: [true, true],
});
/** @param Minimum confidence value ([0.0, 1.0]) from the landmark-tracking model for the hand landmarks to be considered tracked successfully, or otherwise hand detection will be invoked automatically on the next input image. Setting it to a higher value can increase robustness of the solution, at the expense of a higher latency. Ignored if static_image_mode is true, where hand detection simply runs on every image */
minTrackingConfidence = ParamConfig.FLOAT(DEFAULT.minTrackingConfidence, {
range: [0, 1],
rangeLocked: [true, true],
});
};
}
function locateFile(file: string) {
return `https://cdn.jsdelivr.net/npm/@mediapipe/hands/${file}`;
}
function attributes(object: Object3D): HandTrackingObjectAttributes {
const coreObjectClass = coreObjectClassFactory(object);
const selfieMode = coreObjectClass.attribValue(object, CoreComputerVisionHandAttribute.SELFIE_MODE);
const maxNumHands = coreObjectClass.attribValue(object, CoreComputerVisionHandAttribute.MAX_NUM_HANDS);
const modelComplexity = coreObjectClass.attribValue(object, CoreComputerVisionHandAttribute.MODEL_COMPLEXITY);
const minDetectionConfidence = coreObjectClass.attribValue(
object,
CoreComputerVisionHandAttribute.MIN_DETECTION_CONFIDENCE
);
const minTrackingConfidence = coreObjectClass.attribValue(
object,
CoreComputerVisionHandAttribute.MAX_TRACKING_CONFIDENCE
);
const data = {
selfieMode: isBoolean(selfieMode) ? selfieMode : DEFAULT.selfieMode,
maxNumHands: isNumber(maxNumHands) ? maxNumHands : DEFAULT.maxNumHands,
modelComplexity: isBoolean(modelComplexity) ? modelComplexity : DEFAULT.modelComplexity,
minDetectionConfidence: isNumber(minDetectionConfidence)
? minDetectionConfidence
: DEFAULT.minDetectionConfidence,
minTrackingConfidence: isNumber(minTrackingConfidence) ? minTrackingConfidence : DEFAULT.minTrackingConfidence,
};
return data;
}
function trackerOptions(attributes: HandTrackingObjectAttributes): Options {
return {
selfieMode: attributes.selfieMode,
maxNumHands: attributes.maxNumHands,
modelComplexity: attributes.modelComplexity ? 1 : 0,
minDetectionConfidence: attributes.minDetectionConfidence,
minTrackingConfidence: attributes.minTrackingConfidence,
};
}
function createKey(object: Object3D) {
return JSON.stringify(attributes(object));
}
interface ConvertedResult {
multiHandLandmarks: Vector4[];
multiHandWorldLandmarks: Vector4[];
score: number;
side: number;
}
type ConvertedResults = ConvertedResult[];
function createConvertedResult(): ConvertedResult {
const pointsCount = DEFAULT_POSITION.length / 3;
const multiHandLandmarks: Vector4[] = new Array(pointsCount);
const multiHandWorldLandmarks: Vector4[] = new Array(pointsCount);
for (let i = 0; i < pointsCount; i++) {
multiHandLandmarks[i] = new Vector4();
multiHandWorldLandmarks[i] = new Vector4();
}
return {
multiHandLandmarks,
multiHandWorldLandmarks,
score: 0,
side: 0,
};
}
function updateConvertedResult(convertedResult: ConvertedResult, results: Results, index: number) {
//
const multiHandLandmarks = results.multiHandLandmarks[index];
for (let i = 0; i < multiHandLandmarks.length; i++) {
const landmark = multiHandLandmarks[i];
convertedResult.multiHandLandmarks[i].set(
landmark.x,
1 - landmark.y,
landmark.z,
landmark.visibility != null ? landmark.visibility : 0
);
}
//
const multiHandWorldLandmarks = results.multiHandWorldLandmarks[index];
for (let i = 0; i < multiHandWorldLandmarks.length; i++) {
const landmark = multiHandWorldLandmarks[i];
convertedResult.multiHandWorldLandmarks[i].set(
landmark.x,
landmark.y,
landmark.z,
landmark.visibility != null ? landmark.visibility : 0
);
}
//
const handedness = results.multiHandedness[index];
convertedResult.score = handedness.score;
convertedResult.side = handedness.label == 'Right' ? 1 : 0;
}
class TrackerContainer {
private _inProgress: boolean = false;
public results: ConvertedResults = [];
constructor(private tracker: Hands) {
for (let i = 0; i < 3; i++) {
this.results.push(createConvertedResult());
}
tracker.onResults((results: Results) => {
this._inProgress = false;
const subResultsCount = results.multiHandLandmarks.length;
for (let i = 0; i < subResultsCount; i++) {
updateConvertedResult(this.results[i], results, i);
}
});
}
track(source: ComputerVisionValidSource) {
if (this._inProgress) {
return;
}
this._inProgress = true;
this.tracker.send({image: source});
}
}
export class CoreComputerVisionHand {
private static trackerByKey: Map<string, TrackerContainer> = new Map();
private static trackerForObject(object: Object3D): TrackerContainer {
const key = this.trackerKey(object);
let tracker = this.trackerByKey.get(key);
if (!tracker) {
tracker = this._createTracker(trackerOptions(attributes(object)));
this.trackerByKey.set(key, tracker);
}
return tracker;
}
static trackMedia(object: Object3D, source: ComputerVisionValidSource) {
const tracker = this.trackerForObject(object);
tracker.track(source);
}
static trackerResults(object: Object3D) {
return this.trackerForObject(object).results;
}
private static _createTracker(options: Options) {
const hands = new Hands({
locateFile,
});
hands.setOptions(options);
return new TrackerContainer(hands);
}
static trackerKey(object: Object3D): string {
const coreObjectClass = coreObjectClassFactory(object);
let key = coreObjectClass.attribValue(object, CoreComputerVisionHandAttribute.KEY);
if (!key || !isString(key)) {
key = createKey(object);
coreObjectClass.addAttribute(object, CoreComputerVisionHandAttribute.KEY, key);
}
return key;
}
static setAttributes(object: Object3D, options: HandTrackingObjectAttributes) {
const coreObjectClass = coreObjectClassFactory(object);
coreObjectClass.addAttribute(object, CoreComputerVisionHandAttribute.SELFIE_MODE, options.selfieMode);
coreObjectClass.addAttribute(object, CoreComputerVisionHandAttribute.MAX_NUM_HANDS, options.maxNumHands);
coreObjectClass.addAttribute(object, CoreComputerVisionHandAttribute.MODEL_COMPLEXITY, options.modelComplexity);
coreObjectClass.addAttribute(
object,
CoreComputerVisionHandAttribute.MIN_DETECTION_CONFIDENCE,
options.minDetectionConfidence
);
coreObjectClass.addAttribute(
object,
CoreComputerVisionHandAttribute.MAX_TRACKING_CONFIDENCE,
options.minTrackingConfidence
);
}
}