Face++ API实现手势识别系统设计

\'\'\'
# -*- coding:utf-8 -*-
@author: TulLing
\'\'\'
import requests 
from json import JSONDecoder 
 
gesture_englist = [\'big_v\',\'fist\',\'double_finger_up\',\'hand_open\',\'heart_d\',\'index_finger_up\',\'ok\',\'phonecall\',\'palm_up\',\'rock\',\'thumb_down\',\'thumb_up\',\'victory\']
gesture_chinese = [\"我最帅\",
            \"拳头，停下\",
            \"我发誓\",
            \"数字5\",
            \"比心\",
            \"数字1\",
            \"好的呢，OK\",
            \"打电话\",
            \"手心向上\",
            \"爱你，520\",
            \"差评，不好的\",
            \"好评，Good，很棒\",
            \"胜利，开心\"]
# 将字典排序
def sort_dict(adict):
  return sorted(adict.items(),key= lambda item:item[1])
 
class Gesture( ):
  def __init__(self):
    self.http_url = \'https://api-cn.faceplusplus.com/humanbodypp/beta/gesture\'
    self.key = \'*****\'
    self.secret = \'******\'
    self.data = {\"api_key\":self.key,\"api_secret\":self.secret}
 
  
  # 获取手势信息
  def get_info(self,files):
    response = requests.post(self.http_url,data=self.data,files=files)
    req_con = response.content.decode(\'utf-8\')
    req_dict = JSONDecoder().decode(req_con)
    #print(req_dict)
    if(\'error_message\' not in req_dict.keys()) and (len(req_dict[\'hands\'])):
    # 获取
      hands_dict = req_dict[\'hands\']
      #print(type(hands_dict))
      # 获取到手的矩形的字典
      gesture_rectangle_dict = hands_dict[0][\'hand_rectangle\']
      # 获取到手势的字典
      gesture_dict = hands_dict[0][\'gesture\']
      
      return gesture_dict,gesture_rectangle_dict
    else:
      return [],[];
  
  # 获取到手势文本信息
  def get_text(self,index):
    return gesture_chinese[index]
  
  # 获取到手势对应的概率
  def get_pro(self,gesture_dict,index):
    # print(gesture_dict)
    if(gesture_dict is None or gesture_dict == []):
      return 0
    return gesture_dict[gesture_englist[index]]
  
  # 获取到手势的位置
  def get_rectangle(self,gesture_rectangle_dict):
    if(gesture_rectangle_dict is None or gesture_rectangle_dict == []):
      return (0,0,0,0)
    x = gesture_rectangle_dict[\'top\']
    y = gesture_rectangle_dict[\'left\']
    width = gesture_rectangle_dict[\'width\']
    height = gesture_rectangle_dict[\'height\']
    return (x,y,width,height)

\'\'\'
# -*- coding:utf-8 -*-
@author: TulLing
\'\'\'
import sys
sys.path.append(\"../gesture/\")
 
import os
import random
import cv2 as cv
import time
import LearnGesture
 
def gestureLearning():
  os.system(\"cls\")
  print(\"进入学习手势模式！\")
  print(\"我们有13个手势，来和我学吧！(每次结束后可以选择输入 Q\\q 退出！)\")
  while(True):
    pic_num = random.randint(0,12)  # 生成显示的图片的编号(随机数： 0 - 13)
    print(pic_num)
    pic_path = \'../gesture/pic/gesture\' + str(pic_num) + \".jpg\"  # 生成图片路径
    
    pic = cv.imread(pic_path)    # 加载图片
    pic = cv.resize(pic,(120,120))
    cv.imshow(\"PIC\",pic) # 显示要学习的手势
    
    print(\"即将打开摄像头，你有5秒种的时间准备手势，5秒种保持手势！\")
    write_path = \"../gesture/pic/test.jpg\"
    cap = cv.VideoCapture(1)
    while(True):
      _,  = cap.read()
      cv.imshow(\" \", )
      key = cv.waitKey(10)
      if(key == ord(\'Q\') or key == ord(\'q\')):
        cv.imwrite(write_path, )
        cv.waitKey(200)
        cap.release()
        cv.destroyAllWindows()
        break
        
    # 此处应该有手势识别
    files = {\"image_file\":open(write_path,\'rb\')}
    gesture = LearnGesture.Gesture()
    
    # 获取到手势文本
    ge_text = gesture.get_text(pic_num)
    # 获取手势信息
    gesture_dict,gesture_rectangle_dict = gesture.get_info(files)
    # 获取手势的概率
    ge_pro = gesture.get_pro(gesture_dict,pic_num)
    # 获取到手势的坐标
    ge_rect = gesture.get_rectangle(gesture_rectangle_dict)
    print(\"您学习的手势是：\",ge_text)
    print(\"相似度达到：\",ge_pro)
    print(\"具体位置：\",ge_rect)
    
  
    # print(\"一轮学习结束，是否继续学习？(Y/N)\")
    # 退出程序，回到主菜单或者继续
    commend = input(\"一轮学习结束，是否继续学习？(Y/N)：\")
    print(commend)
 
    if( commend == \'N\' or commend == \"n\"):
      break
gestureLearning()