src/backends/insightface_backend.py

import numpy as np
import cv2
from insightface.app import FaceAnalysis

_app = None


def _get_app():
    global _app
    if _app is None:
        _app = FaceAnalysis(providers=["CPUExecutionProvider"])
        _app.prepare(ctx_id=0, det_size=(640, 640))
    return _app


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 _get_face(app, path):
    img = cv2.imread(path)
    if img is None:
        raise ValueError(f"Could not read image: {path}")
    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    faces = app.get(img_rgb)
    if not faces:
        raise ValueError(f"No face detected in image: {path}")
    return faces[0]


def analyze(father_path, mother_path, child_path):
    app = _get_app()

    child_face = _get_face(app, child_path)
    father_face = _get_face(app, father_path)
    mother_face = _get_face(app, mother_path)

    return {
        "age": int(child_face.age),
        "father_score": _to_pct(_cosine_sim(child_face.embedding, father_face.embedding)),
        "mother_score": _to_pct(_cosine_sim(child_face.embedding, mother_face.embedding)),
    }