def __init__(self,useGUI=False,debugWin=True,
drawFaceRct=True,
faceRecognize=True,faceRecognizeXmlfile=None):
self._useGUI=useGUI
self._debugWin=debugWin
self.drawFaceRct=drawFaceRct
#self.drawMoveRct=drawMoveRct
self.faceRecongnize=faceRecognize
self._recognizeFace_xml_file=faceRecognizeXmlfile
self._front=IOSteam()
self._detectFace=FaceTracker()
self._recognizeFace=cv2.createLBPHFaceRecognizer(neighbors=8)
self.displayFrame=None
try:
self._recognizeFace.load(self._recognizeFace_xml_file)
except:
logging.debug('[-]recognize DB xml file:{} fail to load'.format(
self._recognizeFace_xml_file))
logging.info( '[-]without DB xml ,recognize may be reported Error!')
#self._trackers=[]
self._faceLost=False
#self._faceReg_api=API(API_KEY, API_SECRET)
self._res=[]
self._mode=self.Available_Mode[0]
self.faceSetinSameFrame=[]
self.faceSetofImageinSameFrame=[]
self.faceSetofImageinSameFrameResized=[]
class core(object):
Available_Mode=['train','recognize']
Uniform_Size=(40,40)
def __init__(self,useGUI=False,debugWin=True,
drawFaceRct=True,
faceRecognize=True,faceRecognizeXmlfile=None):
self._useGUI=useGUI
self._debugWin=debugWin
self.drawFaceRct=drawFaceRct
#self.drawMoveRct=drawMoveRct
self.faceRecongnize=faceRecognize
self._recognizeFace_xml_file=faceRecognizeXmlfile
self._front=IOSteam()
self._detectFace=FaceTracker()
self._recognizeFace=cv2.createLBPHFaceRecognizer(neighbors=8)
self.displayFrame=None
try:
self._recognizeFace.load(self._recognizeFace_xml_file)
except:
logging.debug('[-]recognize DB xml file:{} fail to load'.format(
self._recognizeFace_xml_file))
logging.info( '[-]without DB xml ,recognize may be reported Error!')
#self._trackers=[]
self._faceLost=False
#self._faceReg_api=API(API_KEY, API_SECRET)
self._res=[]
self._mode=self.Available_Mode[0]
self.faceSetinSameFrame=[]
self.faceSetofImageinSameFrame=[]
self.faceSetofImageinSameFrameResized=[]
def _resize_to_Uniform_Size(self,frame):
return cv2.resize(frame,self.Uniform_Size)
def _face_detection(self,frame):
#backup display
#self._res=[]
self.displayFrame=frame.copy()
self._detectFace.update(frame)
faces=self._detectFace.faces
self.faceSetinSameFrame=[face.faceRect for face in faces]
if(self.faceSetinSameFrame!=[]):
logging.info('faceSetinSameFrame :{}'.format(self.faceSetinSameFrame))
self.faceSetofImageinSameFrame=[i.faceImage for i in faces]
self.faceSetofImageinSameFrameResized=list(map( self._resize_to_Uniform_Size,
self.faceSetofImageinSameFrame ))
if(self.drawFaceRct):
self._detectFace.drawDebugRects(self.displayFrame)
def _main_recognize_once(self,frame):
self._face_detection(frame)
#if self._faceLost:
# self._detectFace.update(frame)
# faces=self._detectFace.faces
# self.faceSetinSameFrame=[face.faceRect for face in faces]
# if(self.faceSetinSameFrame!=[]):
# self.faceSetofImageinSameFrame=[i.faceImage for i in faces]
# self.faceSetofImageinSameFrameResized=list(map( self._resize_to_Uniform_Size,
# self.faceSetofImageinSameFrame )
# )
if(self.faceSetinSameFrame!=[]):
#recognize mode
res=[]
self._res=[]
for i in self.faceSetofImageinSameFrameResized:
res.append(self._recognizeFace.predict(i))
#load result (Rectzone,(may be the person,confidence))
for facezone,whomheis in zip(self.faceSetinSameFrame,res ):
self._res.append(dict(zone=facezone,who=whomheis ))
logging.info('FaceRecognize result: {}'.format(self._res))
#result has been saved.
#else:
#logging.info('Noface found')
def _main_train_once(self,frame,label):
"""
only accept One integer label to train.
"""
if(type(label)!=int):
raise TypeError('label {} must be an integer'.format(label))
self._face_detection(frame)
# self._detectFace.update(frame)
# faces=self._detectFace.faces
# faceSetinSameFrame=[face.faceRect for face in faces]
if(self.faceSetinSameFrame!=[]):
# faceSetofImageinSameFrame=[i.faceImage for i in faces]
# faceSetofImageinSameFrameResized=list(map( self._resize_to_Uniform_Size,
# faceSetofImageinSameFrame )
# )
xlabel=np.asarray([label,], dtype=np.int32)
self._recognizeFace.update([self.faceSetofImageinSameFrameResized[0],],xlabel)
logging.info('faceUpdated {}'.format(xlabel))
def train(self,frame,label):
self._main_train_once(frame,label)
def saveTrainSet(self,filename=None):
if filename!=None:
_filename=filename
else:
_filename=self._recognizeFace_xml_file
if _filename!=None:
self._recognizeFace.save(_filename)
else:
logging.debug('No file Name for _recognizeFace_xml_file!')
def recognize(self,frame):
self._main_recognize_once(frame)
@property
def result(self):
return self._res
