def face_identify(tmp):
global current_uid
global current_ufname
global current_face_emotion
global CONSUMER_KEY
global CONSUMER_SECRET
global ACCESS_TOKEN
global REFRESH_TOKEN
detected_personid = ''
cascPath = 'C:\\Users\\ADMIN\\SM\\haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascPath)
ramp_frames = 10
print ("Face identification started ..........")
cam = cv2.VideoCapture(1)
try:
while True:
for i in range(ramp_frames):
s, im = cam.read()
ret,image = cam.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
#cv2.imshow('Recognizing you...', gray)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.CASCADE_SCALE_IMAGE
)
# Draw a rectangle around the faces
max_area = 0
mx = 0
my = 0
mh = 0
mw = 0
for (x, y, w, h) in faces:
#cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
if w*h > max_area:
mx = x
my = y
mh = h
mw = w
max_area=w*h
if max_area>=15000:
image_crop = image[my:my+mh,mx:mx+mw]
file_name = id_generator()+'.jpg'
file = os.path.join(tmp_path,file_name)
cloudinary_url=cloudinary_tmp + '/' + file_name
cv2.imwrite(file, image_crop)
imup.upload_image(file,file_name)
faceid=msface.face_detect(cloudinary_url)
faceEmotion=msface.emotion_detect(cloudinary_url)
if faceEmotion=='happiness':
faceEmotion='happy'
elif faceEmotion=='sadness':
faceEmotion='sad'
elif faceEmotion=='disgust':
faceEmotion='disgusting'
print ("faceId = " + str(faceid))
print("Emotion detected = " + str(faceEmotion))
detected_personid = msface.face_identify(faceid)
print ("detected_personid = " + str(detected_personid))
else:
continue
if detected_personid:
comm = "SELECT * FROM user WHERE personid = '%s'" % detected_personid
res = cursor.execute(comm)
res = cursor.fetchone()
if res:
CONSUMER_KEY=res[8]
CONSUMER_SECRET=res[9]
ACCESS_TOKEN=res[10]
REFRESH_TOKEN=res[11]
current_uid = res[7]
current_ufname = res[1]
fname = res[1]
current_face_emotion=faceEmotion
print ("Welcome "+fname+"!"+"You are feeling "+current_face_emotion+" today!")
return
else:
print ("person id not found in database")
else:
print ("Unknown person found")
except Exception as e:
print ("Errors occured !")
print (e)
cam.release()
cv2.destroyAllWindows()
def update_dynamic_frame(self):
global current_userid
global current_userfname
detected_personid = ''
welcome_names=''
ramp_frames = 10
print "Face identification started .........."
cv2.destroyAllWindows()
try:
for i in xrange(ramp_frames):
s, im = self.capture.read()
ret,frame = self.capture.read()
#self.message_label.setText('Image Captured')
self.capture_cnt+=1
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(80, 80),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)
print "Total Faces in Image = %d " % len(faces)
#self.message_label.setText("Total Faces in Image = %d " % len(faces))
if len(faces) > 0:
detected_persons = []
persons = []
persons_cnt=0
detected_persons_cnt=0
for (x, y, w, h) in faces:
if w*h>500:
persons_cnt+=1
image_crop = frame[y:y+h,x:x+w]
#self.message_label.setText("Processing.. %d " % persons_cnt)
file_name = id_generator()+'.jpg'
file = os.path.join(tmp_path,file_name)
cloudinary_url=cloudinary_tmp + '/' + file_name
cv2.imwrite(file, image_crop)
imup.upload_image(file,file_name)
faceid=msface.face_detect(cloudinary_url)
print "Result for person %d " % persons_cnt
print "Image File = " + str(file)
print "faceId = " + str(faceid)
detected_personid = msface.face_identify(faceid)
if detected_personid:
print "detected_personid = " + str(detected_personid)
comm = "SELECT * FROM %s WHERE personid = '%s'" % (TABLE_NAME,detected_personid)
res = cursor.execute(comm)
res = cursor.fetchone()
if res:
userid = res[0]
uname = res[1]
fname = res[2]
lname = res[3]
print "Welcome %s !" % (fname+' '+lname)
detected_persons_cnt+=1
detected_persons.append(fname)
persons.append(fname)
now = datetime.datetime.now()
comm = "SELECT * FROM users_present WHERE userid = %d and date = '%s' " % (int(userid), now.strftime("%Y-%m-%d"))
#print comm
res2=cursor.execute(comm)
res2=cursor.fetchone()
if res2==None:
format_str = "INSERT INTO users_present (id, userid) VALUES (NULL,%d)" %(int(userid))
#print format_str
conn.execute(format_str)
conn.commit()
print "Attendance marked for user %s " % uname
else
print "Attendance already marked for user %s " % uname
else:
time_str=strftime("%Y-%m-%d_%H:%M:%S", gmtime())
print "Unknown person found"
cv2.imwrite(os.path.join(unknown_user_path,'cam1_'+time_str+'.jpg'),image_crop)
persons.append('Unknown')
if detected_persons_cnt > 1:
for i in range(detected_persons_cnt-1):
welcome_names = welcome_names + detected_persons[i] + ', '
welcome_names=welcome_names[:-2]
welcome_names=welcome_names + ' & ' + detected_persons[detected_persons_cnt-1]
elif detected_persons_cnt>0:
welcome_names = detected_persons[0]
self.label2.setText('Hello '+ welcome_names)
else:
self.label2.setText('')
print "No person in image"
k=0
for (x, y, w, h) in faces:
if persons[k]!='Unknown':
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame, persons[k],(x, y-10), cv2.FONT_HERSHEY_COMPLEX_SMALL , 1,(0,255,0),1)
else:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
cv2.putText(frame, persons[k],(x, y-10), cv2.FONT_HERSHEY_COMPLEX_SMALL , 1,(0,0,255),1)
k=k+1
#image=cv2.flip(frame, 1)
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
face_image = QImage(image, image.shape[1], image.shape[0],
image.strides[0], QImage.Format_RGB888)
self.face_image.setPixmap(QPixmap.fromImage(face_image))
except Exception as e:
print "Errors occured !"
print e
def face_verify(self, personid):
print "Face identification started .........."
self.capture = cv2.VideoCapture(camera_port)
self.capturing = True
faceid = ''
detected_personid = ''
try:
r, frame = self.capture.read()
frame = cv2.flip(frame, 1)
#cv2.imshow('Video', frame)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
if len(faces) > 0:
max_area = 0
mx = 0
my = 0
mh = 0
mw = 0
for (x, y, w, h) in faces:
if w * h > max_area:
mx = x
my = y
mh = h
mw = w
max_area = w * h
print max_area
image_crop = frame[my:my + mh, mx:mx + mw]
file_name = id_generator() + '.jpg'
file = os.path.join(tmp_path, file_name)
cloudinary_url = cloudinary_tmp + '/' + file_name
cv2.imwrite(file, image_crop)
imup.upload_image(file, file_name)
faceid = msface.face_detect(cloudinary_url)
print "faceId = " + str(faceid)
detected_personid = msface.face_identify(faceid)
print "detected_personid = " + str(detected_personid)
print "personid = " + str(personid)
if detected_personid:
if detected_personid == personid:
print "Face verified sucessfully"
self.capture.release()
return True
else:
print "Other person found"
self.capture.release()
return False
else:
print "Unknown person found"
self.capture.release()
return False
else:
print "No person found"
self.capture.release()
return False
except Exception as e:
print "Errors occured !"
print e
self.capture.release()
return False
def face_identify(tmp):
global current_userid
global current_userfname
detected_personid = ''
camera_port = 1
cascPath = 'haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascPath)
ramp_frames = 10
print "Face identification started .........."
cam = cv2.VideoCapture(camera_port)
try:
while True:
for i in xrange(ramp_frames):
s, im = cam.read()
ret, image = cam.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
# Draw a rectangle around the faces
max_area = 0
mx = 0
my = 0
mh = 0
mw = 0
for (x, y, w, h) in faces:
#cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
if w * h > max_area:
mx = x
my = y
mh = h
mw = w
max_area = w * h
#cv2.imshow('Video', image)
if max_area >= 15000:
image_crop = image[my:my + mh, mx:mx + mw]
file_name = id_generator() + '.jpg'
file = os.path.join(tmp_path, file_name)
cloudinary_url = cloudinary_tmp + '/' + file_name
cv2.imwrite(file, image_crop)
imup.upload_image(file, file_name)
faceid = msface.face_detect(cloudinary_url)
print "faceId = " + str(faceid)
detected_personid = msface.face_identify(faceid)
print "detected_personid = " + str(detected_personid)
else:
continue
if detected_personid:
comm = "SELECT * FROM users WHERE personid = '%s'" % detected_personid
res = cursor.execute(comm)
res = cursor.fetchone()
if res:
current_userid = res[0]
current_userfname = res[2]
fname = res[2]
print "Welcome %s !" % fname
return
else:
print "person id not found in database"
else:
print "Unknown person found"
except Exception as e:
print "Errors occured !"
print e
cam.release()
cv2.destroyAllWindows()
def face_upload(imgPath, fileName):
try:
print 'Uploading...'
imup.upload_image(imgPath, fileName)
except Exception as e:
print("Error: %s" % e.message)