import cv2
import mediapipe as mp

import analysisPoint as mp_drawing
mp_holistic = mp.solutions.holistic
import numpy as np

class MediapipeProcess:

  def mediapipe_det(image,holistic):

    '''
    调用模型推理获得检测结果
    '''

    image.flags.writeable = False
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    results = holistic.process(image)

    return results

  def get_analysis_result(image,results):

    '''
    images: 检测的图片
    results: 图片的检测结果
    对上述结果进行分析
    '''

    image.flags.writeable = True
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

    # face_result = mp_drawing.draw_landmarks(
    #           image,
    #           results.face_landmarks,
    #           mp_holistic.FACEMESH_CONTOURS)    
    
    right_hand_result = mp_drawing.draw_landmarks(
              image,
              results.right_hand_landmarks,
              mp_holistic.HAND_CONNECTIONS)

    left_hand_result = mp_drawing.draw_landmarks(
              image,
              results.left_hand_landmarks,
              mp_holistic.HAND_CONNECTIONS)
    
    # face_bbox = MediapipeProcess.point_to_bbox(face_result)
    right_hand_bbox = MediapipeProcess.point_to_bbox(right_hand_result)
    left_hand_bbox = MediapipeProcess.point_to_bbox(left_hand_result)

    result_dict = {'hand_bbox':[right_hand_bbox,left_hand_bbox]}

    return result_dict

  def point_to_bbox(result_list):
      
    '''
    根据关键点坐标，获取坐标点的最小外接矩形
    '''
      
    result_array = np.array(result_list)
      
    if result_array.all():

      rect = cv2.minAreaRect(result_array) # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）
      bbox = cv2.boxPoints(rect) # 获取最小外接矩形的4个顶点坐标(ps: cv2.boxPoints(rect) for OpenCV 3.x)
      bbox = np.int0(bbox)
      bbox=bbox.tolist()

      left_top = [min(bbox, key=lambda p: p[0])[0], min(bbox, key=lambda p: p[1])[1]]
      right_bottom = [max(bbox, key=lambda p: p[0])[0], max(bbox, key=lambda p: p[1])[1]]

      bbox_list = left_top + right_bottom

 
      return bbox_list