import cv2
import mediapipe as mp
import numpy as np

class MediaPipeDetector:
    def __init__(self, model_complexity=1, min_detection_confidence=0.5):
        self.mp_pose = mp.solutions.pose
        self.pose = self.mp_pose.Pose(
            static_image_mode=False,
            model_complexity=model_complexity,
            enable_segmentation=False,
            min_detection_confidence=min_detection_confidence
        )
        self.mp_drawing = mp.solutions.drawing_utils

    def detect(self, image):
        """Возвращает словарь с ключами: success, landmarks (33,4), pose_landmarks (для отрисовки)"""
        rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        results = self.pose.process(rgb)

        if results.pose_landmarks:
            h, w, _ = image.shape
            landmarks = []
            for lm in results.pose_landmarks.landmark:
                x = lm.x * w
                y = lm.y * h
                z = lm.z
                v = lm.visibility
                landmarks.append([x, y, z, v])
            landmarks = np.array(landmarks, dtype=np.float32)
            return {'success': True, 'landmarks': landmarks, 'pose_landmarks': results.pose_landmarks}
        else:
            return {'success': False, 'landmarks': None, 'pose_landmarks': None}

    def draw_landmarks(self, image, pose_landmarks):
        """Рисует скелет на копии изображения и возвращает её"""
        if pose_landmarks is None:
            return image.copy()
        vis = image.copy()
        self.mp_drawing.draw_landmarks(vis, pose_landmarks, self.mp_pose.POSE_CONNECTIONS)
        return vis