Files
picpeak/backend/__tests__/integration/facePrivacy.test.js
T
Paul Nothaft bbce3cd2a2 feat(faces): let the photographer choose which photo represents a person (#1119)
Phase 1 of #1096.

Clustering picks the cover, and its idea of a good one and a human's do not
always agree. A cluster whose avatar is turned away or softer than the rest
stays that way in the guest-facing people strip too, and nothing in the UI
could change it.

A picker reachable from each person row, reusing the face list the split
dialog already loads — same query, same grid, different action on a click.

Making the choice actually stick took four changes
---------------------------------------------------------------------------
event_people.cover_face_id has existed since migration 177 and the PATCH
already accepted it, so the first version of this was frontend-only. It was
also a no-op:

- facePeopleService.listPeople SELECTED cover_face_id and then discarded it,
  recomputing the cover as the best-scoring VISIBLE face on every read. The
  picker saved, said so, and the avatar reverted immediately. It now prefers
  the stored pick whenever this audience can see it, and falls back to the
  score-ordered choice otherwise — so visibility scoping still wins, and a
  guest is never handed a crop of a photo they cannot open.
- recomputeCentroid overwrote cover_face_id unconditionally. It runs on
  rescan and on photo replacement, so any reprocessing silently undid a
  deliberate choice. It now keeps the chosen face while it is still a member
  of the cluster.
- The face list is cached per person, and split/merge move faces between
  people. Until now the only reader closed itself after acting, so nobody saw
  the stale copy; the picker is a second reader of the same key.
- cover_face_id meant two things. assignFaces seeded it with whichever face
  opened the cluster and recomputeCentroid overwrote it with the highest
  scoring one, so an automatic guess was indistinguishable from a deliberate
  choice — and honouring it would have pinned every UNCURATED person to that
  guess, which is worse than the fallback it replaced (the fallback is
  computed per audience and skips photos a guest cannot open). Both writers
  are gone, migration 179 clears the stored guesses, and the column now means
  one thing. That also removes the need to defend the choice against rescans:
  nothing overwrites it, and a dangling id self-heals to the derived cover.

Clearing existing values is safe rather than destructive: no install has ever
been able to SET a cover, so every stored value is an automatic guess by
construction.

Also fixes a PostgreSQL-only 500
---------------------------------------------------------------------------
GET /admin/events/:id/people/:personId/faces joined `photos` but did not
table-qualify its WHERE, and photo_faces and photos BOTH have an event_id:

  column reference "event_id" is ambiguous

Postgres refuses it, so the endpoint 500s and the Split dialog — its only
consumer until now — has been broken on every PostgreSQL install since the
join was added. SQLite resolves the ambiguity silently, which is why the suite
stayed green. Reproduced against a real Postgres before and after.

The query is now a named builder the route calls and the test imports, rather
than a copy: an earlier version of that test re-declared the query, so the
route could regress to the bare form while the assertions kept passing.

Merge and recluster preserve the choice as well. Both already carried labels
and privacy flags across; the chosen cover is human state of the same kind, so
it now rides along — through a merge when the target has none, and through a
recluster by following its FACE into whichever cluster ends up holding it,
rather than the majority-descendant rule the label uses.

The picker and the endpoint disagree past 500 faces, so the picker now says
when it is showing a capped list rather than presenting it as exhaustive.

Frontend suite 178 passing, backend 23 across the touched suites, build clean,
no new type errors. Mutation-checked twice: dropping the cover preference fails
the new listPeople test while the visibility-scoping test still passes, and
restoring the auto-seed in assignFaces fails it too.
2026-08-21 19:26:52 +02:00

416 lines
18 KiB
JavaScript

/**
* Privacy and visibility guarantees for face recognition (#1074).
*
* These are the tests that matter most in this feature. Two of them cover
* defects that would be invisible in normal use:
*
* - The people strip is computed from face rows, which have no concept of
* photo visibility. Handing a guest a raw count leaks how many hidden
* photos someone appears in, and a cover face picked without scoping
* renders a crop of a photo the guest may not open.
*
* - Face embeddings are biometric data. They must not ride along in a
* .picpeak export, which gets handed to clients and moved between
* operators.
*/
const path = require('path');
const fs = require('fs');
const os = require('os');
process.env.NODE_ENV = 'test';
process.env.TEST_DATABASE_PATH = path.join(
fs.mkdtempSync(path.join(os.tmpdir(), 'picpeak-faceprivacy-')), 'db.sqlite',
);
process.env.JWT_SECRET = process.env.JWT_SECRET || 'faceprivacy-test-secret';
const { bootCrmDb } = require('./helpers/crmDb');
let db; let cleanup; let clustering; let peopleService; let faceProcessor;
function makeEmbedding(id, variant = 0, dim = 64) {
const vec = new Float32Array(dim);
for (let i = 0; i < dim; i++) {
vec[i] = Math.sin((i + 1) * (id + 1) * 0.7) + variant * 0.02 * Math.cos(i * 3.1);
}
let norm = 0;
for (let i = 0; i < dim; i++) norm += vec[i] * vec[i];
norm = Math.sqrt(norm);
for (let i = 0; i < dim; i++) vec[i] /= norm;
return vec;
}
async function seedEvent(slug) {
const [row] = await db('events').insert({
slug,
event_type: 'wedding',
event_name: slug,
event_date: '2026-01-01',
host_email: 'h@example.com',
admin_email: 'a@example.com',
password_hash: 'x',
share_link: `${slug}-share`,
expires_at: new Date().toISOString(),
face_recognition_enabled: true,
}).returning('id');
return typeof row === 'object' ? row.id : row;
}
async function addPhotoWithFace(eventId, embedding, { visibility = 'visible', score = 0.99 } = {}) {
const [p] = await db('photos').insert({
event_id: eventId,
filename: `${Math.random()}.jpg`,
path: '/tmp/x.jpg',
type: 'individual',
visibility,
processing_status: 'complete',
}).returning('id');
const photoId = typeof p === 'object' ? p.id : p;
const row = {
photo_id: photoId,
event_id: eventId,
bbox_x: 0, bbox_y: 0, bbox_w: 200, bbox_h: 200,
det_score: score,
embedding: clustering.packEmbedding(embedding),
model_version: 'test-v1',
created_at: new Date().toISOString(),
};
const [f] = await db('photo_faces').insert(row).returning('id');
return { photoId, face: { ...row, id: typeof f === 'object' ? f.id : f } };
}
describe('face privacy and visibility (#1074)', () => {
beforeAll(async () => {
({ db, cleanup } = await bootCrmDb());
clustering = require('../../src/services/faceClustering');
peopleService = require('../../src/services/facePeopleService');
faceProcessor = require('../../src/services/faceProcessor');
}, 120000);
afterAll(async () => { if (cleanup) await cleanup(); });
describe('visibility scoping', () => {
it('counts only photos the audience can actually see', async () => {
const eventId = await seedEvent('visibility-count');
const faces = [];
// Same person: 3 visible photos, 4 hidden ones.
for (let v = 0; v < 3; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(1, v))).face);
}
for (let v = 3; v < 7; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(1, v), { visibility: 'hidden' })).face);
}
await clustering.assignFaces(eventId, faces);
const guestView = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
const clientView = await peopleService.listPeople(eventId, { isClient: true, minClusterSize: 1 });
expect(guestView).toHaveLength(1);
// The leak this test exists to prevent: 3, never 7.
expect(guestView[0].face_count).toBe(3);
expect(clientView[0].face_count).toBe(7);
});
it('never returns face_count_total to a guest', async () => {
const eventId = await seedEvent('no-total-leak');
const { face } = await addPhotoWithFace(eventId, makeEmbedding(2));
await clustering.assignFaces(eventId, [face]);
const [person] = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
expect(person).not.toHaveProperty('total_face_count');
expect(person).not.toHaveProperty('is_hidden');
});
it('picks a cover face from a photo the guest may open', async () => {
const eventId = await seedEvent('cover-scoping');
// The BEST face (highest score) is in a hidden photo — a naive
// implementation would hand its crop to the guest.
const hidden = await addPhotoWithFace(eventId, makeEmbedding(3, 0), {
visibility: 'hidden', score: 0.99,
});
const visible = await addPhotoWithFace(eventId, makeEmbedding(3, 1), {
visibility: 'visible', score: 0.80,
});
await clustering.assignFaces(eventId, [hidden.face, visible.face]);
const [guestPerson] = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
expect(guestPerson.cover.photo_id).toBe(visible.photoId);
expect(guestPerson.cover.photo_id).not.toBe(hidden.photoId);
});
it('prefers the cover the photographer chose (#1096)', async () => {
const eventId = await seedEvent('chosen-cover');
// The auto-pick would take the 0.99 face. The photographer picked the
// other one — without this the PATCH saved, the toast said so, and the
// avatar reverted on the very next read.
const best = await addPhotoWithFace(eventId, makeEmbedding(9, 0), { score: 0.99 });
const chosen = await addPhotoWithFace(eventId, makeEmbedding(9, 1), { score: 0.70 });
await clustering.assignFaces(eventId, [best.face, chosen.face]);
const [before] = await peopleService.listPeople(eventId, { isClient: true, minClusterSize: 1 });
expect(before.cover.photo_id).toBe(best.photoId);
// Clustering must not have written one: an automatic seed here would be
// indistinguishable from a real choice the moment listPeople honours it.
const seeded = await db('event_people').where({ id: before.id }).first();
expect(seeded.cover_face_id).toBeFalsy();
await db('event_people').where({ id: before.id }).update({ cover_face_id: chosen.face.id });
const [after] = await peopleService.listPeople(eventId, { isClient: true, minClusterSize: 1 });
expect(after.cover.photo_id).toBe(chosen.photoId);
});
it('carries a chosen cover through a merge', async () => {
const eventId = await seedEvent('cover-merge');
const a = await addPhotoWithFace(eventId, makeEmbedding(20, 0), { score: 0.90 });
const b = await addPhotoWithFace(eventId, makeEmbedding(60, 0), { score: 0.95 });
await clustering.assignFaces(eventId, [a.face]);
await clustering.assignFaces(eventId, [b.face]);
const people = await db('event_people').where({ event_id: eventId }).orderBy('id');
expect(people.length).toBeGreaterThan(1);
// The SOURCE carries the choice; the target has none.
await db('event_people').where({ id: people[1].id }).update({ cover_face_id: b.face.id });
await clustering.mergePeople(eventId, [people[1].id], people[0].id);
const target = await db('event_people').where({ id: people[0].id }).first();
expect(target.cover_face_id).toBe(b.face.id);
});
it('carries a chosen cover through a recluster', async () => {
const eventId = await seedEvent('cover-recluster');
const faces = [];
for (let v = 0; v < 3; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(21, v), { score: 0.9 - v * 0.1 })).face);
}
await clustering.assignFaces(eventId, faces);
const [person] = await db('event_people').where({ event_id: eventId });
// Pick the WORST-scoring face, so an automatic re-pick would differ.
const chosen = faces[2].id;
await db('event_people').where({ id: person.id }).update({ cover_face_id: chosen });
await clustering.recluster(eventId);
const after = await db('event_people').where({ event_id: eventId }).whereNotNull('cover_face_id');
expect(after).toHaveLength(1);
expect(after[0].cover_face_id).toBe(chosen);
});
it('falls back to a visible face when the chosen cover is hidden from this audience', async () => {
const eventId = await seedEvent('chosen-cover-hidden');
// Choosing a cover must never override the visibility scoping — that
// would hand a guest a crop of a photo they cannot open.
const hidden = await addPhotoWithFace(eventId, makeEmbedding(10, 0), {
visibility: 'hidden', score: 0.99,
});
const visible = await addPhotoWithFace(eventId, makeEmbedding(10, 1), { score: 0.70 });
await clustering.assignFaces(eventId, [hidden.face, visible.face]);
const [person] = await peopleService.listPeople(eventId, { isClient: true, minClusterSize: 1 });
await db('event_people').where({ id: person.id }).update({ cover_face_id: hidden.face.id });
const [guestView] = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
expect(guestView.cover.photo_id).toBe(visible.photoId);
expect(guestView.cover.photo_id).not.toBe(hidden.photoId);
});
it('drops a person entirely when all their photos are hidden', async () => {
const eventId = await seedEvent('all-hidden');
const faces = [];
for (let v = 0; v < 3; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(4, v), { visibility: 'hidden' })).face);
}
await clustering.assignFaces(eventId, faces);
const guestView = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
expect(guestView).toHaveLength(0);
const clientView = await peopleService.listPeople(eventId, { isClient: true, minClusterSize: 1 });
expect(clientView).toHaveLength(1);
});
it('omits hidden and ignored people from the guest response', async () => {
const eventId = await seedEvent('hidden-people');
const a = (await addPhotoWithFace(eventId, makeEmbedding(5))).face;
const b = (await addPhotoWithFace(eventId, makeEmbedding(6))).face;
await clustering.assignFaces(eventId, [a, b]);
const people = await db('event_people').where({ event_id: eventId }).orderBy('id');
await db('event_people').where({ id: people[0].id }).update({ is_hidden: true });
await db('event_people').where({ id: people[1].id }).update({ is_ignored: true });
const guestView = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 1 });
expect(guestView).toHaveLength(0);
const adminView = await peopleService.listPeople(eventId, { isClient: true, forAdmin: true });
expect(adminView).toHaveLength(2);
});
it('does not attach a hidden person to a photo a guest can see', async () => {
const eventId = await seedEvent('person-ids-hidden');
const { photoId, face } = await addPhotoWithFace(eventId, makeEmbedding(7));
await clustering.assignFaces(eventId, [face]);
const person = await db('event_people').where({ event_id: eventId }).first();
await db('event_people').where({ id: person.id }).update({ is_hidden: true });
const guestMap = await peopleService.getPersonIdsByPhoto(eventId, [photoId], { forAdmin: false });
expect(guestMap.get(photoId)).toBeUndefined();
const adminMap = await peopleService.getPersonIdsByPhoto(eventId, [photoId], { forAdmin: true });
expect(adminMap.get(photoId)).toEqual([person.id]);
});
it('respects the minimum cluster size so one-off bystanders stay out', async () => {
const eventId = await seedEvent('min-cluster');
const solo = (await addPhotoWithFace(eventId, makeEmbedding(8))).face;
const crowd = [];
for (let v = 0; v < 4; v++) {
crowd.push((await addPhotoWithFace(eventId, makeEmbedding(9, v))).face);
}
await clustering.assignFaces(eventId, [solo, ...crowd]);
const people = await peopleService.listPeople(eventId, { isClient: false, minClusterSize: 3 });
expect(people).toHaveLength(1);
expect(people[0].face_count).toBe(4);
});
});
describe('erasure', () => {
it('purgeEvent removes every face row and resets the photos', async () => {
const eventId = await seedEvent('purge');
const faces = [];
for (let v = 0; v < 3; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(10, v))).face);
}
await clustering.assignFaces(eventId, faces);
await db('photos').where({ event_id: eventId }).update({ face_status: 'done', face_count: 1 });
expect(await db('photo_faces').where({ event_id: eventId })).not.toHaveLength(0);
expect(await db('event_people').where({ event_id: eventId })).not.toHaveLength(0);
await faceProcessor.purgeEvent(eventId);
expect(await db('photo_faces').where({ event_id: eventId })).toHaveLength(0);
expect(await db('event_people').where({ event_id: eventId })).toHaveLength(0);
const photos = await db('photos').where({ event_id: eventId });
expect(photos.every((p) => p.face_status === null && p.face_count === null)).toBe(true);
});
it('purgePhotoFaces removes face rows WITHOUT relying on the FK cascade', async () => {
// The regression this guards: PicPeak does not enable
// `PRAGMA foreign_keys` on SQLite, so ON DELETE CASCADE never fires
// there and biometric embeddings outlived the photo. The pragma is
// explicitly OFF here so the assertion can only pass if the deletion
// path purges the rows itself.
await db.raw('PRAGMA foreign_keys = OFF');
const eventId = await seedEvent('purge-no-cascade');
const faces = [];
for (let v = 0; v < 3; v++) {
faces.push((await addPhotoWithFace(eventId, makeEmbedding(20, v))).face);
}
await clustering.assignFaces(eventId, faces);
const person = await db('event_people').where({ event_id: eventId }).first();
expect(person.face_count_total).toBe(3);
const victim = faces[0];
await faceProcessor.purgePhotoFaces(victim.photo_id);
expect(await db('photo_faces').where({ photo_id: victim.photo_id })).toHaveLength(0);
// …and the person it belonged to was rebuilt, not left with a stale count.
const after = await db('event_people').where({ id: person.id }).first();
expect(after.face_count_total).toBe(2);
});
it('purging the last face of a person removes the person too', async () => {
await db.raw('PRAGMA foreign_keys = OFF');
const eventId = await seedEvent('purge-last-face');
const { face, photoId } = await addPhotoWithFace(eventId, makeEmbedding(21));
await clustering.assignFaces(eventId, [face]);
expect(await db('event_people').where({ event_id: eventId })).toHaveLength(1);
await faceProcessor.purgePhotoFaces(photoId);
expect(await db('event_people').where({ event_id: eventId })).toHaveLength(0);
});
it('deleting an event removes its people and faces', async () => {
await db.raw('PRAGMA foreign_keys = ON');
const eventId = await seedEvent('event-delete');
const { face } = await addPhotoWithFace(eventId, makeEmbedding(11));
await clustering.assignFaces(eventId, [face]);
await db('photos').where({ event_id: eventId }).del();
await db('events').where({ id: eventId }).del();
expect(await db('photo_faces').where({ event_id: eventId })).toHaveLength(0);
expect(await db('event_people').where({ event_id: eventId })).toHaveLength(0);
});
});
describe('all-in-one image block (#1042 / PR #1068)', () => {
// Blocked for performance: the AIO image runs backend, frontend, SQLite
// and every worker in one container, with no ML sidecar to talk to. The
// failure there would not be loud — just a slow install that looks
// broken — so the gate is asserted rather than assumed.
const faceSettings = require('../../src/services/faceSettings');
afterEach(() => { delete process.env.PICPEAK_SINGLE_CONTAINER; });
it('reports the feature off regardless of the flag row', async () => {
process.env.PICPEAK_SINGLE_CONTAINER = 'true';
expect(faceSettings.isSingleContainerImage()).toBe(true);
// Even with the flag ON in the database.
await db('feature_flags').insert({ key: 'faces', value: true })
.onConflict('key').merge()
.catch(async () => {
await db('feature_flags').where({ key: 'faces' }).update({ value: true });
});
expect(await faceSettings.isFeatureEnabled()).toBe(false);
});
it('refuses per-event detection too', async () => {
process.env.PICPEAK_SINGLE_CONTAINER = 'true';
const eventId = await seedEvent('aio-block');
const event = await db('events').where({ id: eventId }).first();
expect(event.face_recognition_enabled).toBeTruthy();
expect(await faceSettings.isEnabledForEvent(event)).toBe(false);
});
it('accepts only explicit truthy markers', () => {
for (const v of ['true', '1', 'yes', 'TRUE']) {
process.env.PICPEAK_SINGLE_CONTAINER = v;
expect(faceSettings.isSingleContainerImage()).toBe(true);
}
for (const v of ['false', '0', '', 'no']) {
process.env.PICPEAK_SINGLE_CONTAINER = v;
expect(faceSettings.isSingleContainerImage()).toBe(false);
}
delete process.env.PICPEAK_SINGLE_CONTAINER;
expect(faceSettings.isSingleContainerImage()).toBe(false);
});
});
describe('export and backup exclusion', () => {
it('excludes both face tables from .picpeak exports', () => {
const { EXCLUDED_TABLES } = require('../../src/services/picpeakExportService');
expect(EXCLUDED_TABLES.has('photo_faces')).toBe(true);
expect(EXCLUDED_TABLES.has('event_people')).toBe(true);
});
it('excludes both face tables from the database backup table list', async () => {
const databaseBackup = require('../../src/services/databaseBackup');
const service = databaseBackup.DatabaseBackupService
? new databaseBackup.DatabaseBackupService()
: databaseBackup;
if (typeof service.getTables !== 'function') return; // shape differs; covered by the export test
const tables = await service.getTables();
expect(tables).not.toContain('photo_faces');
expect(tables).not.toContain('event_people');
// Sanity: the filter didn't eat everything.
expect(tables).toContain('events');
});
});
});