Files
traxxx/src/biometrics.js
2026-07-05 20:57:00 +02:00

206 lines
5.2 KiB
JavaScript

'use strict';
const config = require('config');
const path = require('path');
const fsPromises = require('fs').promises;
const Human = require('@vladmandic/human').default;
const knex = require('./knex');
const logger = require('./logger')(__filename);
const humanConfig = {
modelBasePath: `file://${path.join(__dirname, '../node_modules/@vladmandic/human/models')}/`,
backend: 'tensorflow', // uses tfjs-node under the hood
face: {
enabled: true,
detector: { rotation: false },
mesh: { enabled: false },
iris: { enabled: false },
description: { enabled: true },
emotion: { enabled: true },
},
body: { enabled: false },
hand: { enabled: false },
gesture: { enabled: false },
};
let humanInstance = null;
const nsPerSec = 1e9;
async function getHumanInstance() {
if (!humanInstance) {
humanInstance = new Human(humanConfig);
await humanInstance.load();
await humanInstance.warmup();
}
return humanInstance;
}
async function getImageBuffer(mediaEntry) {
if (mediaEntry.is_s3) {
if (!config.s3.enabled) {
logger.verbose(`Skipping biometrics for ${mediaEntry.media_id}, S3 not enabled`);
return null;
}
const res = await fetch(`https://${config.s3.bucket}/${mediaEntry.path}`);
if (res.ok) {
return Buffer.from(await res.arrayBuffer());
}
return null;
}
try {
const buffer = await fsPromises.readFile(path.join(config.media.path, mediaEntry.path));
return buffer;
} catch (_error) {
return null;
}
}
async function getBiometrics(avatarEntry) {
if (!avatarEntry) {
return null;
}
const human = await getHumanInstance();
const buffer = await getImageBuffer(avatarEntry);
if (!buffer) {
return null;
}
let tensor;
try {
tensor = human.tf.node.decodeImage(buffer, 3);
const result = await human.detect(tensor);
return result;
} catch (error) {
logger.error(error);
return null;
} finally {
tensor.dispose();
}
}
function getAvatarSource(actorIds, includePhotos) {
if (includePhotos) {
return knex('actors_avatars')
.select('actor_id', 'media_id')
.modify((builder) => {
if (actorIds) {
builder.whereIn('actor_id', actorIds);
}
});
}
return knex('actors')
.select('id as actor_id', 'avatar_media_id as media_id')
.whereNotNull('avatar_media_id')
.modify((builder) => {
if (actorIds) {
builder.whereIn('id', actorIds);
}
});
}
async function setBiometrics(actorIds, shouldUpdate = false, includePhotos = false) {
if (!config.media.biometrics.enabled) {
return;
}
const startTime = process.hrtime();
const avatarSource = getAvatarSource(actorIds, includePhotos);
const avatarEntries = await knex
.select(
'avatar_source.actor_id',
'media.id as media_id',
'media.path',
'media.is_s3',
knex.raw('coalesce(json_agg(media_biometrics.biometrics) filter (where media_biometrics.id is not null), \'[]\') as biometrics'),
)
.from(avatarSource.as('avatar_source'))
.leftJoin('media', 'media.id', 'avatar_source.media_id')
.leftJoin('media_biometrics', 'media_biometrics.media_id', 'media.id')
.groupBy('avatar_source.actor_id', 'media.id', 'media.path', 'media.is_s3');
await avatarEntries.reduce(async (chain, avatarEntry, avatarIndex) => {
await chain;
if (avatarEntry.biometrics.length > 0 && !shouldUpdate) {
logger.verbose(`Skipping biometrics for ${avatarEntry.media_id}, already present`);
return;
}
const biometrics = await getBiometrics(avatarEntry);
if (!biometrics) {
return;
}
const curatedBiometrics = biometrics.face.map((face) => ({
biometrics: {
age: face.age,
gender: face.gender,
genderScore: face.genderScore,
emotion: face.emotion,
box: face.box,
score: face.score,
...Object.fromEntries(Object.entries(face.annotations).map(([key, annotation]) => [key, annotation.filter(Boolean)[0] || null])),
},
embedding: face.embedding,
}));
if (curatedBiometrics.length === 0) {
return;
}
if (shouldUpdate) {
await knex('media_biometrics')
.where('media_id', avatarEntry.media_id)
.delete();
}
await knex('media_biometrics')
.insert(curatedBiometrics.map((face, index) => ({
media_id: avatarEntry.media_id,
face_index: index,
width: biometrics.width,
height: biometrics.height,
biometrics: JSON.stringify(face.biometrics),
embedding: knex.raw('?::vector', [JSON.stringify(face.embedding)]),
updated_at: knex.raw('now()'),
})))
.onConflict(['media_id', 'face_index'])
.ignore();
const processed = avatarIndex + 1;
const [elapsedSec, elapsedNs] = process.hrtime(startTime);
const elapsedMs = (elapsedSec * nsPerSec + elapsedNs) / 1e6;
const avgMsPerEntry = elapsedMs / processed;
const remainingMs = avgMsPerEntry * (avatarEntries.length - processed);
const remainingMinutes = (remainingMs / 1000 / 60).toFixed(1);
logger.info(`Set biometrics for ${avatarEntry.media_id} (${processed}/${avatarEntries.length}, ~${remainingMinutes}m remaining)`);
}, Promise.resolve());
const diffTime = process.hrtime(startTime);
const totalMs = (diffTime[0] * nsPerSec + diffTime[1]) / 1e6;
logger.info(`Biometrics done in ${(totalMs / 1000).toFixed(1)}s for ${actorIds?.length || 'all'} actors and ${avatarEntries.length} avatars`);
}
module.exports = {
setBiometrics,
};