import joblib
import numpy as np
from ml_gestures.feature_extractor import normalize_landmarks

class MLGesturePredictor:
    def __init__(self, model_path, class_names):
        data = joblib.load(model_path)
        self.model = data['model']
        self.class_names = data['class_names']
        if 'none' not in self.class_names:
            self.class_names.append('none')   # запасной вариант

    def predict(self, landmarks):
        features = normalize_landmarks(landmarks).reshape(1, -1)
        pred_id = self.model.predict(features)[0]
        if pred_id < len(self.class_names):
            return self.class_names[pred_id]
        return 'none'