def startMainLoop(self):
verbose = False
self.video = VideoWindow(WINDOW_TITLE)
### CONFIGURATION ###
# Extract init template and threshold
initTemplate = self.__extractTemplate(INIT_TEXT)
if initTemplate == None:
return
# Extract start template and threshold
startTemplate = self.__extractTemplate(START_TEXT)
if startTemplate == None:
return
initSearcherParams = []
#initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_SHAPE)
initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_COLOR)
initSearcher = InitTemplateSearcher(initTemplate, initSearcherParams)
hsvInit = cv2.cvtColor(initTemplate, cv2.COLOR_BGR2HSV)
skinSearcher = SkinDetection(hsvInit, showSkin=True)
startSearcherParams = []
startSearcherParams.append(StartTemplateSearcher.INIT_MATCHER_COLOR)
startSearcher = StartTemplateSearcher(startTemplate, startTemplate)
### START MAIN LOOP ###
initBackgroundprob = 0
startBackgroundprob = 0
started = False
trajectoryID = 0
trajectoryStartTime = 0
initThreshold = 0
startThreshold = 0
while True:
img = self.__getFrame__()
initProb, initLoc = initSearcher.matchInitTemplate(img, verbose)
hsvImg = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
skinResult = skinSearcher.simpleMatch(hsvImg,
wholePictureGiven=True,
loc=initLoc,
showSkin=True)
# if initBackgroundprob == 0:
# print 'background not set'
# elif initProb > initBackgroundprob*3:
# print 'background prob:\t'+str(initBackgroundprob)
# print 'initprob:\t'+str(initProb)
if initThreshold == 0:
a = 1
#print 'init not calibrated'
elif (initProb >= initThreshold * 0.9) and skinResult:
print 'init prob:\t' + str(initProb)
print 'init thres:\t' + str(initThreshold)
common.playSound('beep-10.wav')
# not started yet, get it started
if started == False:
started = True
trajectoryID = 1
trajectoryStartTime = time.time()
self.__skipFrames__(5)
img = self.__getFrame__()
else:
started = False
trajectoryStartTime = time.time()
startProb, startLoc = startSearcher.matchInitTemplate(
img, verbose)
datapoint = TrajectoryPoint(
-2, startLoc,
time.time() - trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.__skipFrames__(5)
img = self.__getFrame__()
if started == True:
startProb, startLoc = startSearcher.matchInitTemplate(
img, verbose)
if startProb >= startThreshold * 0.9:
self.video.drawTextonImg(img, startLoc, str(startProb))
cv2.rectangle(img, startLoc,
(startLoc[0] + startTemplate.shape[1],
startLoc[1] + startTemplate.shape[0]),
(0, 255, 0))
datapoint = TrajectoryPoint(
trajectoryID, startLoc,
time.time() - trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.video.drawTextonImg(
img, initLoc, 'skin Match: ' + str(skinResult) +
' templateMATCH: ' + str(initProb))
cv2.rectangle(img, initLoc, (initLoc[0] + initTemplate.shape[1],
initLoc[1] + initTemplate.shape[0]),
(255, 255, 0))
self.video.showImg(img)
key = cv2.waitKey(1)
key = key % 256
# init = i = 105
# start = s = 115
# background = space = 32
# print = p = 112
# escape button pressed
if key == 27:
self.video.destroyWindow()
self.capture.release()
return -1
# print images
if key == 112:
self.video.writeImg(img, "image.jpg")
self.video.writeImg(initTemplate, "inittemplate.jpg")
self.video.writeImg(startTemplate, "starttemplate.jpg")
# calibrate init
if key == 105:
initThreshold = self.__extractForeground(
initTemplate, initSearcher, INIT_CALIBRATE)
print 'init threshold:\t' + str(initThreshold)
self.__skipFrames__(15, APPLICATION_STARTED)
# calibrate start
if key == 115:
startThreshold = self.__extractForeground(
startTemplate, startSearcher, START_CALIBRATE)
print 'start threshold:\t' + str(startThreshold)
self.__skipFrames__(15)
def startMainLoop(self):
verbose = False
self.video = VideoWindow(WINDOW_TITLE)
### CONFIGURATION ###
# Extract init template and threshold
initTemplate = self.__extractTemplate(INIT_TEXT)
if initTemplate == None:
return
# Extract start template and threshold
startTemplate = self.__extractTemplate(START_TEXT)
if startTemplate == None:
return
initSearcherParams = []
#initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_SHAPE)
initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_COLOR)
initSearcher = InitTemplateSearcher(initTemplate, initSearcherParams)
hsvInit = cv2.cvtColor(initTemplate,cv2.COLOR_BGR2HSV)
skinSearcher = SkinDetection(hsvInit, showSkin= True);
startSearcherParams = []
startSearcherParams.append(StartTemplateSearcher.INIT_MATCHER_COLOR)
startSearcher = StartTemplateSearcher(startTemplate, startTemplate)
### START MAIN LOOP ###
initBackgroundprob = 0
startBackgroundprob = 0
started = False
trajectoryID = 0
trajectoryStartTime = 0
initThreshold = 0
startThreshold = 0
while True:
img = self.__getFrame__()
initProb, initLoc = initSearcher.matchInitTemplate(img, verbose)
hsvImg = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
skinResult = skinSearcher.simpleMatch(hsvImg, wholePictureGiven = True, loc =initLoc, showSkin = True)
# if initBackgroundprob == 0:
# print 'background not set'
# elif initProb > initBackgroundprob*3:
# print 'background prob:\t'+str(initBackgroundprob)
# print 'initprob:\t'+str(initProb)
if initThreshold == 0:
a=1
#print 'init not calibrated'
elif (initProb >= initThreshold*0.9) and skinResult:
print 'init prob:\t'+str(initProb)
print 'init thres:\t'+str(initThreshold)
common.playSound('beep-10.wav')
# not started yet, get it started
if started == False:
started = True
trajectoryID = 1
trajectoryStartTime = time.time()
self.__skipFrames__(5)
img = self.__getFrame__()
else:
started = False
trajectoryStartTime = time.time()
startProb, startLoc = startSearcher.matchInitTemplate(img, verbose)
datapoint = TrajectoryPoint(-2,startLoc,time.time()-trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.__skipFrames__(5)
img = self.__getFrame__()
if started == True:
startProb, startLoc = startSearcher.matchInitTemplate(img, verbose)
if startProb >= startThreshold*0.9:
self.video.drawTextonImg(img, startLoc, str(startProb))
cv2.rectangle(img, startLoc, (startLoc[0]+startTemplate.shape[1], startLoc[1]+startTemplate.shape[0]), (0,255,0))
datapoint = TrajectoryPoint(trajectoryID,startLoc,time.time()-trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.video.drawTextonImg(img, initLoc,'skin Match: ' + str(skinResult) +' templateMATCH: ' + str(initProb) )
cv2.rectangle(img, initLoc, (initLoc[0]+initTemplate.shape[1], initLoc[1]+initTemplate.shape[0]), (255,255,0))
self.video.showImg(img)
key = cv2.waitKey(1)
key = key%256
# init = i = 105
# start = s = 115
# background = space = 32
# print = p = 112
# escape button pressed
if key == 27:
self.video.destroyWindow()
self.capture.release()
return -1
# print images
if key == 112:
self.video.writeImg(img, "image.jpg")
self.video.writeImg(initTemplate, "inittemplate.jpg")
self.video.writeImg(startTemplate, "starttemplate.jpg")
# calibrate init
if key == 105:
initThreshold = self.__extractForeground(initTemplate, initSearcher, INIT_CALIBRATE)
print 'init threshold:\t'+str(initThreshold)
self.__skipFrames__(15,APPLICATION_STARTED )
# calibrate start
if key == 115:
startThreshold = self.__extractForeground(startTemplate, startSearcher, START_CALIBRATE)
print 'start threshold:\t'+str(startThreshold)
self.__skipFrames__(15)
class Handcommands(object):
def __init__(self, trajectoryQueue):
self.trajectoryQueue = trajectoryQueue
self.capture = cv2.VideoCapture(0)
self.capture.set(cv2.cv.CV_CAP_PROP_GAIN, 0)
self.initProb = 0
self.startProb = 0
self.dummyProb = 0
self.filterWeight = 0.1
self.crossValidSize = 100
self.crossValidWeight = 2.0
def __getFrame__(self):
img = self.capture.read()[1]
#img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY,dstCn=1)
#img = cv2.equalizeHist(img)
#img = cv2.GaussianBlur(img,(3,3),1)
img = cv2.medianBlur(img, 3)
return img
def __skipFrames__(self, frameCount, text=None):
index = 0
while index < frameCount:
img = self.__getFrame__()
if text != None:
self.video.setText(text)
self.video.showImg(img)
cv2.waitKey(1)
index += 1
return self.__getFrame__()
def __extractTemplate(self, text):
template = None
while template == None:
img = self.__getFrame__()
template = self.video.extractMouseArea(img)
self.video.setText(text)
self.video.showImg(img)
key = cv2.waitKey(1)
if key == 27:
self.video.destroyWindow()
self.capture.release()
return None
return template
def __extractBackground(self, template, templateMatcher, text):
n = 50
maxProb = 0
for _ in range(n):
img = self.__getFrame__()
self.video.setText(text)
prob, _ = templateMatcher.matchInitTemplate(img, False)
if prob > maxProb:
maxProb = prob
self.video.showImg(img)
cv2.waitKey(1)
return maxProb
def __extractForeground(self, template, templateMatcher, text):
n = 50
accProb = 0
for _ in range(n):
img = self.__getFrame__()
self.video.setText(text)
prob, _ = templateMatcher.matchInitTemplate(img, False)
accProb += prob
self.video.showImg(img)
cv2.waitKey(1)
return accProb / n
def startMainLoop(self):
verbose = False
self.video = VideoWindow(WINDOW_TITLE)
### CONFIGURATION ###
# Extract init template and threshold
initTemplate = self.__extractTemplate(INIT_TEXT)
if initTemplate == None:
return
# Extract start template and threshold
startTemplate = self.__extractTemplate(START_TEXT)
if startTemplate == None:
return
initSearcherParams = []
#initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_SHAPE)
initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_COLOR)
initSearcher = InitTemplateSearcher(initTemplate, initSearcherParams)
hsvInit = cv2.cvtColor(initTemplate, cv2.COLOR_BGR2HSV)
skinSearcher = SkinDetection(hsvInit, showSkin=True)
startSearcherParams = []
startSearcherParams.append(StartTemplateSearcher.INIT_MATCHER_COLOR)
startSearcher = StartTemplateSearcher(startTemplate, startTemplate)
### START MAIN LOOP ###
initBackgroundprob = 0
startBackgroundprob = 0
started = False
trajectoryID = 0
trajectoryStartTime = 0
initThreshold = 0
startThreshold = 0
while True:
img = self.__getFrame__()
initProb, initLoc = initSearcher.matchInitTemplate(img, verbose)
hsvImg = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
skinResult = skinSearcher.simpleMatch(hsvImg,
wholePictureGiven=True,
loc=initLoc,
showSkin=True)
# if initBackgroundprob == 0:
# print 'background not set'
# elif initProb > initBackgroundprob*3:
# print 'background prob:\t'+str(initBackgroundprob)
# print 'initprob:\t'+str(initProb)
if initThreshold == 0:
a = 1
#print 'init not calibrated'
elif (initProb >= initThreshold * 0.9) and skinResult:
print 'init prob:\t' + str(initProb)
print 'init thres:\t' + str(initThreshold)
common.playSound('beep-10.wav')
# not started yet, get it started
if started == False:
started = True
trajectoryID = 1
trajectoryStartTime = time.time()
self.__skipFrames__(5)
img = self.__getFrame__()
else:
started = False
trajectoryStartTime = time.time()
startProb, startLoc = startSearcher.matchInitTemplate(
img, verbose)
datapoint = TrajectoryPoint(
-2, startLoc,
time.time() - trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.__skipFrames__(5)
img = self.__getFrame__()
if started == True:
startProb, startLoc = startSearcher.matchInitTemplate(
img, verbose)
if startProb >= startThreshold * 0.9:
self.video.drawTextonImg(img, startLoc, str(startProb))
cv2.rectangle(img, startLoc,
(startLoc[0] + startTemplate.shape[1],
startLoc[1] + startTemplate.shape[0]),
(0, 255, 0))
datapoint = TrajectoryPoint(
trajectoryID, startLoc,
time.time() - trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.video.drawTextonImg(
img, initLoc, 'skin Match: ' + str(skinResult) +
' templateMATCH: ' + str(initProb))
cv2.rectangle(img, initLoc, (initLoc[0] + initTemplate.shape[1],
initLoc[1] + initTemplate.shape[0]),
(255, 255, 0))
self.video.showImg(img)
key = cv2.waitKey(1)
key = key % 256
# init = i = 105
# start = s = 115
# background = space = 32
# print = p = 112
# escape button pressed
if key == 27:
self.video.destroyWindow()
self.capture.release()
return -1
# print images
if key == 112:
self.video.writeImg(img, "image.jpg")
self.video.writeImg(initTemplate, "inittemplate.jpg")
self.video.writeImg(startTemplate, "starttemplate.jpg")
# calibrate init
if key == 105:
initThreshold = self.__extractForeground(
initTemplate, initSearcher, INIT_CALIBRATE)
print 'init threshold:\t' + str(initThreshold)
self.__skipFrames__(15, APPLICATION_STARTED)
# calibrate start
if key == 115:
startThreshold = self.__extractForeground(
startTemplate, startSearcher, START_CALIBRATE)
print 'start threshold:\t' + str(startThreshold)
self.__skipFrames__(15)
class Handcommands(object):
def __init__(self, trajectoryQueue):
self.trajectoryQueue = trajectoryQueue
self.capture = cv2.VideoCapture(0)
self.capture.set(cv2.cv.CV_CAP_PROP_GAIN,0)
self.initProb = 0
self.startProb = 0
self.dummyProb = 0
self.filterWeight = 0.1;
self.crossValidSize = 100
self.crossValidWeight = 2.0
def __getFrame__(self):
img = self.capture.read()[1]
#img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY,dstCn=1)
#img = cv2.equalizeHist(img)
#img = cv2.GaussianBlur(img,(3,3),1)
img = cv2.medianBlur(img, 3)
return img
def __skipFrames__(self, frameCount, text = None):
index = 0
while index<frameCount:
img = self.__getFrame__()
if text != None:
self.video.setText(text)
self.video.showImg(img)
cv2.waitKey(1)
index +=1
return self.__getFrame__()
def __extractTemplate(self, text):
template = None
while template == None:
img = self.__getFrame__()
template = self.video.extractMouseArea(img)
self.video.setText(text)
self.video.showImg(img)
key = cv2.waitKey(1)
if key == 27:
self.video.destroyWindow()
self.capture.release()
return None
return template
def __extractBackground(self,template,templateMatcher, text):
n = 50
maxProb = 0
for _ in range(n):
img = self.__getFrame__()
self.video.setText(text)
prob,_ = templateMatcher.matchInitTemplate(img, False)
if prob > maxProb:
maxProb = prob
self.video.showImg(img)
cv2.waitKey(1)
return maxProb
def __extractForeground(self, template, templateMatcher, text):
n = 50
accProb = 0
for _ in range(n):
img = self.__getFrame__()
self.video.setText(text)
prob,_ = templateMatcher.matchInitTemplate(img, False)
accProb += prob
self.video.showImg(img)
cv2.waitKey(1)
return accProb/n
def startMainLoop(self):
verbose = False
self.video = VideoWindow(WINDOW_TITLE)
### CONFIGURATION ###
# Extract init template and threshold
initTemplate = self.__extractTemplate(INIT_TEXT)
if initTemplate == None:
return
# Extract start template and threshold
startTemplate = self.__extractTemplate(START_TEXT)
if startTemplate == None:
return
initSearcherParams = []
#initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_SHAPE)
initSearcherParams.append(InitTemplateSearcher.INIT_MATCHER_COLOR)
initSearcher = InitTemplateSearcher(initTemplate, initSearcherParams)
hsvInit = cv2.cvtColor(initTemplate,cv2.COLOR_BGR2HSV)
skinSearcher = SkinDetection(hsvInit, showSkin= True);
startSearcherParams = []
startSearcherParams.append(StartTemplateSearcher.INIT_MATCHER_COLOR)
startSearcher = StartTemplateSearcher(startTemplate, startTemplate)
### START MAIN LOOP ###
initBackgroundprob = 0
startBackgroundprob = 0
started = False
trajectoryID = 0
trajectoryStartTime = 0
initThreshold = 0
startThreshold = 0
while True:
img = self.__getFrame__()
initProb, initLoc = initSearcher.matchInitTemplate(img, verbose)
hsvImg = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
skinResult = skinSearcher.simpleMatch(hsvImg, wholePictureGiven = True, loc =initLoc, showSkin = True)
# if initBackgroundprob == 0:
# print 'background not set'
# elif initProb > initBackgroundprob*3:
# print 'background prob:\t'+str(initBackgroundprob)
# print 'initprob:\t'+str(initProb)
if initThreshold == 0:
a=1
#print 'init not calibrated'
elif (initProb >= initThreshold*0.9) and skinResult:
print 'init prob:\t'+str(initProb)
print 'init thres:\t'+str(initThreshold)
common.playSound('beep-10.wav')
# not started yet, get it started
if started == False:
started = True
trajectoryID = 1
trajectoryStartTime = time.time()
self.__skipFrames__(5)
img = self.__getFrame__()
else:
started = False
trajectoryStartTime = time.time()
startProb, startLoc = startSearcher.matchInitTemplate(img, verbose)
datapoint = TrajectoryPoint(-2,startLoc,time.time()-trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.__skipFrames__(5)
img = self.__getFrame__()
if started == True:
startProb, startLoc = startSearcher.matchInitTemplate(img, verbose)
if startProb >= startThreshold*0.9:
self.video.drawTextonImg(img, startLoc, str(startProb))
cv2.rectangle(img, startLoc, (startLoc[0]+startTemplate.shape[1], startLoc[1]+startTemplate.shape[0]), (0,255,0))
datapoint = TrajectoryPoint(trajectoryID,startLoc,time.time()-trajectoryStartTime, startProb)
self.trajectoryQueue.pushDataPoint(datapoint)
self.video.drawTextonImg(img, initLoc,'skin Match: ' + str(skinResult) +' templateMATCH: ' + str(initProb) )
cv2.rectangle(img, initLoc, (initLoc[0]+initTemplate.shape[1], initLoc[1]+initTemplate.shape[0]), (255,255,0))
self.video.showImg(img)
key = cv2.waitKey(1)
key = key%256
# init = i = 105
# start = s = 115
# background = space = 32
# print = p = 112
# escape button pressed
if key == 27:
self.video.destroyWindow()
self.capture.release()
return -1
# print images
if key == 112:
self.video.writeImg(img, "image.jpg")
self.video.writeImg(initTemplate, "inittemplate.jpg")
self.video.writeImg(startTemplate, "starttemplate.jpg")
# calibrate init
if key == 105:
initThreshold = self.__extractForeground(initTemplate, initSearcher, INIT_CALIBRATE)
print 'init threshold:\t'+str(initThreshold)
self.__skipFrames__(15,APPLICATION_STARTED )
# calibrate start
if key == 115:
startThreshold = self.__extractForeground(startTemplate, startSearcher, START_CALIBRATE)
print 'start threshold:\t'+str(startThreshold)
self.__skipFrames__(15)
