class trainLimitFrame(object):
def __init__(self,framelength=100,label=0,xmlfile='./train/mytrainSet.xml'):
self._framelen=framelength
self._xmlfile=xmlfile
self._label=label
self._core=core(faceRecognizeXmlfile=self._xmlfile)
self._iosteam=IOSteam()
self._window=PreviewWindowManager('TrainWindows')
self._window_faceZone=PreviewWindowManager('TrainWindows.FaceZone')
def run(self):
self._window.createWindow()
self._window_faceZone.createWindow()
self._iosteam.run()
for i in range(self._framelen):
logging.info('current frame: {}'.format(i))
frame=self._iosteam.frame
self._core.train(frame,self._label)
# self._core._face_detection(frame)
whattoShow=self._core.displayFrame
self._window.show(whattoShow)
if self._core.faceSetofImageinSameFrameResized!=[]:
self._window_faceZone.show(self._core.faceSetofImageinSameFrameResized[0])
cv2.waitKey(1)
self._iosteam.stop()
self._core.saveTrainSet()
self._window.destroyWindow()
self._window_faceZone.destroyWindow()
def __init__(self,framelength=100,label=0,xmlfile='./train/mytrainSet.xml'):
self._framelen=framelength
self._xmlfile=xmlfile
self._label=label
self._core=core(faceRecognizeXmlfile=self._xmlfile)
self._iosteam=IOSteam()
self._window=PreviewWindowManager('TrainWindows')
self._window_faceZone=PreviewWindowManager('TrainWindows.FaceZone')
def __init__(self,xmlfile='./train/mytrainSet.xml',imgDB='faceDB'):
self._xmlfile=xmlfile
self._trainedImgPostion=imgDB
self._imgMat=[]
self._label=[]
self._core=core(faceRecognizeXmlfile=self._xmlfile)
self._iosteam=IOSteam()
self._window=PreviewWindowManager('TrainWindows',self.onKeypress)
self._window_faceZone=PreviewWindowManager('TrainWindows.FaceZone')
self._trained_file_used=False
self._keep_run=True
self._apply_recognize=False
self.train_setted_img()
class application(object):
def __init__(self,xmlfile='./train/mytrainSet.xml',imgDB='faceDB'):
self._xmlfile=xmlfile
self._trainedImgPostion=imgDB
self._imgMat=[]
self._label=[]
self._core=core(faceRecognizeXmlfile=self._xmlfile)
self._iosteam=IOSteam()
self._window=PreviewWindowManager('TrainWindows',self.onKeypress)
self._window_faceZone=PreviewWindowManager('TrainWindows.FaceZone')
self._trained_file_used=False
self._keep_run=True
self._apply_recognize=False
self.train_setted_img()
def _link_img_lable(self,img,label):
self._imgMat.append(img)
self._label.append(label)
def _load_image_trained(self):
oswalk=list(os.walk(self._trainedImgPostion))
for current_dir,sub_dir,sub_file in oswalk:
if sub_file!=[]:
for eachfile in sub_file:
fileposition=current_dir+'\\'+eachfile
img=cv2.imread(fileposition)
label=current_dir.split('\\')[-1]
self._link_img_lable(img,int(label))
logging.debug('file walker:filePosition:{} label:{}'.format(
fileposition, label ))
def onKeypress(self, keycode):
"""Handle a keypress.
space -> Take a screenshot.
escape -> Quit.
r -> Reverse mode of faceRecognize,(default:off)
m -> Move png file to faceSetDataBase,Please input an integer[1,2,3,4,5...] to tell the programe how to settle current *.png.after operation,png files will be moved to (./faceDB/[label]/i.png)
"""
if keycode == 32: # space
self._iosteam.dumpFrame()
elif keycode == 27: # escape
#self._windowManager.destroyWindow()
self._keep_run=False
elif keycode == ord('r'):
#activate face recognize
self._apply_recognize=not self._apply_recognize
logging.info('[+]app recognize mode change to {}'.format(
self._apply_recognize))
if self._apply_recognize:
#self.train_setted_img()
pass
elif keycode == ord('m'):
#move file .png to label
label=raw_input('[*]Please input the interger ID of current dirs\' photo:\n')
try:
os.mkdir('./faceDB/'+label)
except WindowsError as e:
logging.info('Directory error{},means that existed'.format(e))
filename=[i for i in os.listdir('.') if i.endswith('png')]
logging.info('file:{}'.format(filename))
if 0==os.system('mv *.png ./faceDB/'+label):
logging.info('[+]*.png moved Successfully')
else:
logging.info('[-]*.png moved Fail')
def train_setted_img(self):
"""
run during the init of app,pre train gived image with label
"""
self._load_image_trained()
for i in range(len(self._label)):
self._core.train( self._imgMat[i],self._label[i] )
logging.debug('pre train step used img{} ,label{} '.format(
self._imgMat[i].shape,self._label[i]))
self._trained_file_used=True
def _runwithIOSteam(self):
self._window.createWindow()
self._window_faceZone.createWindow()
self._iosteam.run()
while self._keep_run:
frame=self._iosteam.frame
if(frame==None):
continue
#face recognize
if self._apply_recognize:
self._core.recognize(frame)
result=self._core.result
else:
#just detect faceZone
self._core._face_detection(frame)
#preview result here
whattoShow=self._core.displayFrame
if self._apply_recognize:
self._draw_name_in_frame(whattoShow)
self._window.show(whattoShow)
if self._core.faceSetofImageinSameFrameResized!=[]:
self._window_faceZone.show(self._core.faceSetofImageinSameFrameResized[0])
self._window.processEvents()
self._iosteam.stop()
self._window.destroyWindow()
self._window_faceZone.destroyWindow()
def _draw_name_in_frame(self,frame):
for eachPeople in self._core.result:
true_name=faceIDmatchName[eachPeople['who'][0]]
dist=str(eachPeople['who'][1])
pos=tuple(eachPeople['zone'][:2])
draw_name(frame,true_name+dist,pos)
def run(self):
if(self._trained_file_used):
self._runwithIOSteam()
else:
logging.debug('faceDB do not used in Train')
# -*- coding: utf-8 -*- """ Created on Sun Jun 19 17:33:35 2016 test FaceDetectation @author: pip """ import cv2 import logging from cameraIO import IOSteam import sys from trackers import FaceTracker front=IOSteam() tracker=FaceTracker() front.run() tracker.update( front.frame) facelist=tracker.faces front.stop() print(facelist)