/** * Face algorithm implementation * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline */ import { log, now } from '../util/util'; import { env } from '../util/env'; import * as tf from '../../dist/tfjs.esm.js'; import * as facemesh from './facemesh'; import * as emotion from '../gear/emotion'; import * as faceres from './faceres'; import * as mask from './mask'; import * as antispoof from './antispoof'; import * as liveness from './liveness'; import * as gear from '../gear/gear'; import * as ssrnetAge from '../gear/ssrnet-age'; import * as ssrnetGender from '../gear/ssrnet-gender'; import * as mobilefacenet from './mobilefacenet'; import type { FaceResult } from '../result'; import type { Tensor } from '../tfjs/types'; import type { Human } from '../human'; import { calculateFaceAngle } from './angles'; export const detectFace = async (parent: Human /* instance of human */, input: Tensor): Promise => { // run facemesh, includes blazeface and iris // eslint-disable-next-line no-async-promise-executor let timeStamp; let ageRes; let gearRes; let genderRes; let emotionRes; let mobilefacenetRes; let antispoofRes; let livenessRes; let descRes; const faceRes: Array = []; parent.state = 'run:face'; timeStamp = now(); const faces = await facemesh.predict(input, parent.config); parent.performance.face = env.perfadd ? (parent.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp); if (!input.shape || input.shape.length !== 4) return []; if (!faces) return []; // for (const face of faces) { for (let i = 0; i < faces.length; i++) { parent.analyze('Get Face'); // is something went wrong, skip the face // @ts-ignore possibly undefied if (!faces[i].tensor || faces[i].tensor['isDisposedInternal']) { log('Face object is disposed:', faces[i].tensor); continue; } // optional face mask if (parent.config.face.detector?.mask) { const masked = await mask.mask(faces[i]); tf.dispose(faces[i].tensor); faces[i].tensor = masked as Tensor; } // calculate face angles const rotation = faces[i].mesh && (faces[i].mesh.length > 200) ? calculateFaceAngle(faces[i], [input.shape[2], input.shape[1]]) : null; // run emotion, inherits face from blazeface parent.analyze('Start Emotion:'); if (parent.config.async) { emotionRes = parent.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; } else { parent.state = 'run:emotion'; timeStamp = now(); emotionRes = parent.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; parent.performance.emotion = env.perfadd ? (parent.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp); } parent.analyze('End Emotion:'); // run antispoof, inherits face from blazeface parent.analyze('Start AntiSpoof:'); if (parent.config.async) { antispoofRes = parent.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; } else { parent.state = 'run:antispoof'; timeStamp = now(); antispoofRes = parent.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; parent.performance.antispoof = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp); } parent.analyze('End AntiSpoof:'); // run liveness, inherits face from blazeface parent.analyze('Start Liveness:'); if (parent.config.async) { livenessRes = parent.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; } else { parent.state = 'run:liveness'; timeStamp = now(); livenessRes = parent.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; parent.performance.liveness = env.perfadd ? (parent.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp); } parent.analyze('End Liveness:'); // run gear, inherits face from blazeface parent.analyze('Start GEAR:'); if (parent.config.async) { gearRes = parent.config.face['gear']?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; } else { parent.state = 'run:gear'; timeStamp = now(); gearRes = parent.config.face['gear']?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; parent.performance.gear = Math.trunc(now() - timeStamp); } parent.analyze('End GEAR:'); // run gear, inherits face from blazeface parent.analyze('Start SSRNet:'); if (parent.config.async) { ageRes = parent.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; genderRes = parent.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; } else { parent.state = 'run:ssrnet'; timeStamp = now(); ageRes = parent.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; genderRes = parent.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; parent.performance.ssrnet = Math.trunc(now() - timeStamp); } parent.analyze('End SSRNet:'); // run gear, inherits face from blazeface parent.analyze('Start MobileFaceNet:'); if (parent.config.async) { mobilefacenetRes = parent.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; } else { parent.state = 'run:mobilefacenet'; timeStamp = now(); mobilefacenetRes = parent.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : {}; parent.performance.mobilefacenet = Math.trunc(now() - timeStamp); } parent.analyze('End MobileFaceNet:'); // run emotion, inherits face from blazeface parent.analyze('Start Description:'); if (parent.config.async) { descRes = parent.config.face.description?.enabled ? faceres.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; } else { parent.state = 'run:description'; timeStamp = now(); descRes = parent.config.face.description?.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), parent.config, i, faces.length) : null; parent.performance.description = env.perfadd ? (parent.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp); } parent.analyze('End Description:'); // if async wait for results if (parent.config.async) { [ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes] = await Promise.all([ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes]); } parent.analyze('Finish Face:'); // override age/gender if alternative models are used if (parent.config.face['ssrnet']?.enabled && ageRes && genderRes) descRes = { age: ageRes.age, gender: genderRes.gender, genderScore: genderRes.genderScore }; if (parent.config.face['gear']?.enabled && gearRes) descRes = { age: gearRes.age, gender: gearRes.gender, genderScore: gearRes.genderScore, race: gearRes.race }; // override descriptor if embedding model is used if (parent.config.face['mobilefacenet']?.enabled && mobilefacenetRes) descRes.descriptor = mobilefacenetRes; // calculate iris distance // iris: array[ center, left, top, right, bottom] if (!parent.config.face.iris?.enabled && faces[i]?.annotations?.leftEyeIris && faces[i]?.annotations?.rightEyeIris) { delete faces[i].annotations.leftEyeIris; delete faces[i].annotations.rightEyeIris; } const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0] && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0) && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null)) ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2] : 0; // note: average human iris size is 11.7mm // optionally return tensor const tensor = parent.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null; // dispose original face tensor tf.dispose(faces[i].tensor); // delete temp face image if (faces[i].tensor) delete faces[i].tensor; // combine results const res: FaceResult = { ...faces[i], id: i, }; if (descRes?.age) res.age = descRes.age; if (descRes?.gender) res.gender = descRes.gender; if (descRes?.genderScore) res.genderScore = descRes?.genderScore; if (descRes?.descriptor) res.embedding = descRes?.descriptor; if (descRes?.race) res.race = descRes?.race; if (emotionRes) res.emotion = emotionRes; if (antispoofRes) res.real = antispoofRes; if (livenessRes) res.live = livenessRes; if (irisSize && irisSize !== 0) res.iris = Math.trunc(500 / irisSize / 11.7) / 100; if (rotation) res.rotation = rotation; if (tensor) res.tensor = tensor; faceRes.push(res); parent.analyze('End Face'); } parent.analyze('End FaceMesh:'); if (parent.config.async) { if (parent.performance.face) delete parent.performance.face; if (parent.performance.age) delete parent.performance.age; if (parent.performance.gender) delete parent.performance.gender; if (parent.performance.emotion) delete parent.performance.emotion; } return faceRes; };