src/backends/deepface_backend.py

import numpy as np
from deepface import DeepFace

_MODEL = "VGG-Face"


def _cosine_sim(a, b):
    a, b = np.array(a, dtype=float), np.array(b, dtype=float)
    return float(np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b)))


def _to_pct(sim):
    return round(max(0.0, min(1.0, (sim + 1) / 2)) * 100, 1)


def analyze(father_path, mother_path, child_path):
    child_info = DeepFace.analyze(
        child_path, actions=["age"], enforce_detection=False, silent=True
    )
    age = int(child_info[0]["age"])

    child_emb = DeepFace.represent(
        child_path, model_name=_MODEL, enforce_detection=False
    )[0]["embedding"]
    father_emb = DeepFace.represent(
        father_path, model_name=_MODEL, enforce_detection=False
    )[0]["embedding"]
    mother_emb = DeepFace.represent(
        mother_path, model_name=_MODEL, enforce_detection=False
    )[0]["embedding"]

    return {
        "age": age,
        "father_score": _to_pct(_cosine_sim(child_emb, father_emb)),
        "mother_score": _to_pct(_cosine_sim(child_emb, mother_emb)),
    }