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myVideoProcessing.py
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from myGlobalVariables import *
from myCommonModules import text_save,makeVideoFileName
from sklearn.externals import joblib
from myFrameProcessing import frameProcess
from myMapDemo import baiduMap
import socket
import requests
# 视频处理程序，读本地摄像头，识别手势后将结果发给服务器
# cameraID=0，本地摄像头ID
# 每隔nFrames帧处理一次
# hand_svm_model="hand_svm_model.m"，SVM模型路径
# face_cascade_path，人脸检测模型路径
# useWaterShed=True,手部分割时，启用分水岭算法
# moveSeg=True,启用运动分割检测手部
# GestureSendMode = 'SOCKET',向服务发送识别结果的接口方式，'SOCKET'或'REST'
# ip='127.0.0.1',port=8888，接收手势识别结果的服务器IP地址和端口号,ip=None或不传参，则不连接服务器
# restURL=None,通过REST接口项服务器发送手势识别结果时的URL
# showVideo=True显示视频
# 如果保存视频，用saveVideo=传入保存文件路径
# collectHandData=None不采集手形数据，如需采集手形数据，传入手形名称。
# 在当前目录collectHandData + r'_imgs/'中保存collectHandData + '_' + str(t) + '.jpg'手部图像
# 在当前目录下以collectHandData + '_data.txt'保存特征数据
# 所采集数据供SVM训练用
# demoMap=True,是否启动地图演示
# mapPath，地图网页路径
# chromeDriverPath，ChromeDriver路径
# sensitivity,手势响应灵敏度
def localVideoProcces(cameraID=0, nFrames=2, hand_svm_model=r"..\model\hand_svm_model.m",
face_cascade_path=r"..\model\haarcascade_frontalface_alt2.xml",
handSize=100,useWaterShed=True, moveSeg=True,
GestureSendMode = 'SOCKET',ip=None,port=8888,restURL=None,showVideo=True, saveVideo=None,
collectHandData=None,demoMap=True,mapPath=None, chromeDriverPath=None,sensitivity=1):
c=None # Socket对象初始化为None，以防REST模式下，调用TellSeverClose函数中socket=c参数出错
baseurl='' # baseur赋初值，以防Socket模式下，调用TellSeverClose函数中baseurl参数出错
sendGesture2ServerViaSocket = False # 是否通过Socket向服务器传送手势识别结果的标识
if GestureSendMode=='SOCKET' and ip is not None:
print('正在连接服务器(',ip,':',port,')......')
c = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
conn = c.connect_ex((ip, port))
if conn == 10061:
print('无法与服务器(',ip,':',port,')建立Socket连接，手势识别结果无法通过Socket接口发送到服务器端。')
else:
sendGesture2ServerViaSocket = True
print('已与服务器(',ip,':',port,')建立Socket连接，手势识别结果将同步发送到服务器端。')
sendGesture2ServerViaREST = False # 是否通过REST向服务器传送手势识别结果的标识
if GestureSendMode=='REST' and restURL is not None:
print('将通过REST接口向',restURL,'发送手势识别结果.....')
baseurl = restURL + '?'
sendGesture2ServerViaREST = True
handsvm = None
if not hand_svm_model is None:
if os.path.exists(hand_svm_model):
handsvm = joblib.load(hand_svm_model) # 加载训练好的手形识别svm模型
if demoMap:
mapDemo = baiduMap(mapPath=mapPath, mapType='BMAP_NORMAL_MAP', chromeDriverPath=chromeDriverPath,sensitivity=sensitivity)
demoMap = mapDemo.canDemo
# 读入视频，提取帧图像
cap = cv2.VideoCapture(cameraID)
# 强制视频格式转换，防止YUK格式帧率过低
fourcc=cv2.VideoWriter_fourcc('M', 'J', 'P', 'G')
cap.set(cv2.CAP_PROP_FOURCC, fourcc)
print('FrameWidth:', cap.get(cv2.CAP_PROP_FRAME_WIDTH),', FrameHeight:', cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
hasFrame, frame = cap.read()
lastFrame = np.copy(frame) # 用np.copy(frame)比frame.copy()速度快
# 加载Haar人脸检测器
face_cascade = None
if not face_cascade_path is None:
face_cascade = cv2.CascadeClassifier(face_cascade_path) # 加载级联分类器模型
face_cascade.load(face_cascade_path)
# 保存视频处理结果用
vid_writer = None
if saveVideo:
videofilename = makeVideoFileName(filename=saveVideo)
vid_writer = cv2.VideoWriter(videofilename , cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'), 15,
(frame.shape[1] * 2, frame.shape[0]))
# 创建目录，采集手形数据图像用
if collectHandData:
if not os.path.exists(collectHandData + '_imgs'):
os.makedirs(collectHandData + '_imgs')
if nFrames <= 1: nFrames = 1
lastkey = -1 # 用于判断是否连续按下两次ESC键
k = 0 # 记录处理过的帧数
while cap.isOpened():
k = (k + 1) % 2592000 # 一天重置一次
t = time.time()
hasFrame, currentFrame = cap.read()
if currentFrame is None:
cv2.waitKey()
continue
currentFrame = cv2.flip(currentFrame, 1)
# 跳帧处理，每nFrames帧做一次处理
if k % nFrames == 0:
gesture, cg, lastFrame = frameProcess(currentFrame, lastFrame, handsvm, face_cascade, handSize,
useWaterShed, moveSeg, showVideo,
saveVideo=vid_writer, collectHandData=collectHandData)
if demoMap:
try:
mapDemo.run(command=gesture) # 操控地图
if mapDemo.confirmClose:
TellServerClose(lastkey=27, key=27,
sendGesture2ServerViaSocket=sendGesture2ServerViaSocket,
sendGesture2ServerViaREST=sendGesture2ServerViaREST,
socket=c, baseurl=baseurl)
break
except Exception as e:
print('执行动作出错：', e)
if sendGesture2ServerViaSocket:
try:
c.send(gesture.encode("utf8"))
except Exception as e:
print("服务器连接异常，可能服务器端已经关闭，正在尝试重新连接服务器......")
conn = c.connect_ex((ip, port))
print(conn)
if conn == 10061:
print('无法与服务器(', ip, ':', port, ')建立Socket连接，手势识别结果无法通过Socket接口发送到服务器端。')
sendGesture2ServerViaSocket = False
else:
sendGesture2ServerViaSocket = True
print('已与服务器(', ip, ':', port, ')重新建立Socket连接，手势识别结果将继续同步发送到服务器端。')
if sendGesture2ServerViaREST:
params = {
'gesture': gesture,
'confidence': cg
}
res = requests.get(baseurl, params=params)
# res.encoding = 'utf-8'
# print(res.text)
# 响应键盘，等1ms，按Esc键退出
key = cv2.waitKey(1)
if lastkey == 27:
TellServerClose(lastkey=lastkey,key=key,
sendGesture2ServerViaSocket=sendGesture2ServerViaSocket,
sendGesture2ServerViaREST=sendGesture2ServerViaREST,
socket=c,baseurl=baseurl)
# 保存手形数据，采集训练数据时用
if collectHandData:
text_save(handdata, collectHandData + '_data.txt')
break
lastkey = key
cap.release()
if saveVideo:
vid_writer.release()
print('手势识别结果视频已经记录在文件', videofilename,'中。')
# 告知服务器结束通信
# lastkey=27,key=-1,按了一次ESC键，发送'end'，告知服务器，客户端终止；
# lastkey=27,key=27,连续按了两次ESC键，发送'exit'，命令服务器程序终止。
# sendGesture2ServerViaSocket=True,通知Socket服务器，socket是Socket对象
# sendGesture2ServerViaREST=False,同时REST服务器，baseurl是服务器网址
def TellServerClose(lastkey=27,key=-1,sendGesture2ServerViaSocket=False,sendGesture2ServerViaREST=False,socket=None,baseurl=None):
if lastkey == 27:
if key ==-1:
command='CloseClient'# 按一次ESC，通知服务器，客户端退出
elif key==27:
command='CloseServer'# 连续按两次ESC，通知服务器端程序退出
if sendGesture2ServerViaSocket:
try:
socket.send(command.encode("utf8"))
except Exception as e:
pass
if sendGesture2ServerViaREST:
params = {
'gesture': command,
'confidence': 1
}
try:
res = requests.get(baseurl, params=params)
except Exception as e:
pass