Explicite/api-test

1# app/services/insightface_engine.py2import numpy as np3import cv24from insightface.app import FaceAnalysis5 6_face_app = None7 8def get_face_app():9    global _face_app10    if _face_app is None:11        # name="buffalo_l" es un pack popular (detector+recognition)12        _face_app = FaceAnalysis(name="buffalo_l")13        # ctx_id=-1 => CPU. (Si tuvieras GPU CUDA sería 0)14        _face_app.prepare(ctx_id=-1, det_size=(640, 640))15    return _face_app16 17def pick_best_face(faces):18    """19    Si hay varias caras, escogemos la de mayor área (lo más común).20    """21    if not faces:22        return None23    def area(face):24        x1, y1, x2, y2 = face.bbox.astype(int)25        return max(0, x2-x1) * max(0, y2-y1)26    return max(faces, key=area)27 28def to_bbox_dict(face):29    x1, y1, x2, y2 = face.bbox.astype(int)30    # tu esquema anterior usa top/right/bottom/left31    return {"top": int(y1), "right": int(x2), "bottom": int(y2), "left": int(x1)}32 33def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:34    a = a.astype("float32")35    b = b.astype("float32")36    a = a / (np.linalg.norm(a) + 1e-12)37    b = b / (np.linalg.norm(b) + 1e-12)38    return float(np.dot(a, b))39 40def augment_rgb(np_rgb: np.ndarray, seed: int) -> np.ndarray:41    """42    Variantes suaves: brillo/contraste + rotación leve.43    Esto ayuda cuando hay barba, luz distinta, etc.44    """45    rng = np.random.default_rng(seed)46    img = np_rgb.copy()47 48    # Brillo/contraste49    alpha = float(rng.uniform(0.90, 1.10))   # contraste50    beta = float(rng.uniform(-12, 12))       # brillo51    img = cv2.convertScaleAbs(img, alpha=alpha, beta=beta)52 53    # Rotación leve54    h, w = img.shape[:2]55    angle = float(rng.uniform(-3.0, 3.0))56    M = cv2.getRotationMatrix2D((w / 2, h / 2), angle, 1.0)57    img = cv2.warpAffine(img, M, (w, h), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT)58 59    return img60