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cast a wider net for face similarity #84

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cast a wider net for face similarity #84

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147 changes: 98 additions & 49 deletions src/pages/api/people/[id]/similar-faces.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,8 @@ import { getCurrentUser } from "@/handlers/serverUtils/user.utils";
import { stringToBoolean } from "@/helpers/data.helper";
import { assetFaces, assets, exif, person } from "@/schema";
import { faceSearch } from "@/schema/faceSearch.schema";
import { and, cosineDistance, desc, eq, gt, ne, sql } from "drizzle-orm";
import { and, cosineDistance, desc, eq, gt, ne, sql, avg, count } from "drizzle-orm";
import { PgVector } from "drizzle-orm/pg-core";
import type { NextApiRequest, NextApiResponse } from "next";

type ISortField = "assetCount" | "updatedAt" | "createdAt";
Expand All @@ -23,7 +24,7 @@ export default async function handler(
req: NextApiRequest,
res: NextApiResponse
) {
try {

const {
id,
} = req.query as any as IQuery;
Expand All @@ -42,65 +43,113 @@ export default async function handler(
});
}

const assetFaceRecords = await db
.select()
.from(assetFaces)
.where(eq(assetFaces.personId, personRecord.id))
.limit(1);
const assetFaceRecord = assetFaceRecords?.[0];

if (!assetFaceRecord) {
return res.status(404).json({
error: "Person has no face",
});
}

const faceSearchRecords = await db
.select()
.from(faceSearch)
.where(eq(faceSearch.faceId, assetFaceRecord.id))
.limit(1);
const target_faces = db
.select({
face_id: sql<string>`x.id`.as('face_id'),
person_id: sql<string>`x."personId"`.as('person_id'),
asset_id: sql<string>`x."assetId"`.as('asset_id'),
embedding: sql<vector>`y.embedding`.as('embedding'),
dummy1: sql<number>`1`.as('dummy1')
})
.from(sql`asset_faces AS x`)
.innerJoin(sql`face_search AS y`,
eq(sql`x."id"`, sql`y."faceId"`)
)
.innerJoin(person, eq(person.id, sql<string>`x."personId"`))
.where(
and(
ne(sql`x."personId"`, id)),
eq(person.name, '')
)
.as('target_faces');

const template_faces = db
.select({
face_id: sql<string>`x.id`.as('face_id'),
person_id: sql<string>`x."personId"`.as('person_id'),
embedding: sql<vector>`y.embedding`.as('embedding'),
dummy2: sql<number>`1`.as('dummy2')
})
.from(sql`asset_faces AS x`)
.innerJoin(sql`face_search AS y`,
eq(sql`x."id"`, sql`y."faceId"`)
)
.where(ne(sql`x."personId"`, id))
.orderBy(sql`RANDOM()`)
.limit(10)
.as('template_faces');
console.log('haaa');
const similarity = sql<number>`1 - (${cosineDistance(
sql`target_faces.embedding`,
sql`template_faces.embedding`
)})`.as('similarity');
const pairs = db
.select({
face_id: sql<string>`target_faces.face_id`.as('face_id'),
person_id: sql<string>`target_faces.person_id`.as('person_id'),
template_person_id: sql<string>`template_faces.person_id`.as('template_person_id'),
asset_id: target_faces.asset_id,
similarity
})
.from(target_faces)
.innerJoin(template_faces,
eq(template_faces.dummy2, target_faces.dummy1)
).as('pairs');

const faceSearchRecord = faceSearchRecords?.[0];
if (!faceSearchRecord) {
return res.status(404).json({
error: "No similar faces found",
});
}
console.log('bbb');
const avg_scores = db
.select({
person_id_with_avg_score: pairs.person_id,
avg_score: avg(pairs.similarity),
num_photos: count()
})
.from(pairs)
.where(gt(pairs.similarity, 0.15))
.having(({ num_photos }) => gt(num_photos, 3))
.groupBy(pairs.person_id)
.orderBy(sql`avg(${pairs.similarity}) desc`)
.limit(12).as('avg_scores');
console.log('abg');
console.log(avg_scores);

const similarity = sql<number>`1 - (${cosineDistance(
faceSearch.embedding,
faceSearchRecord.embedding
)})`;

const people = await db
.selectDistinctOn([person.id], {
const all_best = db
.selectDistinctOn([sql`pairs.${pairs.person_id}`], {
id: person.id,
name: person.name,
birthDate: person.birthDate,
isHidden: person.isHidden,
updatedAt: person.updatedAt,
assetId: assetFaces.id,
faceSearch: faceSearch.faceId,
similarity,
assetId: pairs.asset_id,
faceSearch: pairs.face_id,
similarity: pairs.similarity
})
.from(faceSearch)
.leftJoin(assetFaces, eq(assetFaces.id, faceSearch.faceId))
.innerJoin(person, eq(person.id, assetFaces.personId))

.from(pairs)
.innerJoin(avg_scores, eq(sql`avg_scores.${avg_scores.person_id_with_avg_score}`, sql`pairs.${pairs.person_id}`))
.innerJoin(person, eq(person.id, sql`pairs.${pairs.person_id}`))
.where(
and(
ne(person.id, id),
eq(person.ownerId, currentUser.id),
gt(similarity, 0.5)
)
)
.limit(12);
ne(sql`pairs.${pairs.person_id}`, pairs.template_person_id),
gt(pairs.similarity, 0.15)
))
.as('all_best')
//.toSQL();
console.log(all_best);


//console.log('huhuh');
//console.log(all_best?.[0]);


const people = await db
.select()
.from(all_best)
.orderBy(sql`similarity DESC`)
.limit(12);
console.log(people);

return res.status(200).json(people);
} catch (error: any) {
res.status(500).json({
error: error?.message,
});
}


}