def take_attendance():
start=time.time()
period=12
recognizer = cv2.face.LBPHFaceRecognizer_create() # create lpbh face recognizer
recognizer.read('trainer/trainer.yml')
cascadePath = "Cascades/haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath);
font = cv2.FONT_HERSHEY_SIMPLEX
# iniciate id counter
id = 0
#names = [' ', 'Manoj', 'Ram', 'Srijana', 'Sanjay']
# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video width
cam.set(4, 480) # set video height
# Define min window size to be recognized as a face
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
ret, img = cam.read()
img = cv2.flip(img, 1) # Flip vertically
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(int(minW), int(minH)),
)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
ids, confidence = recognizer.predict(gray[y:y + h, x:x + w])
if (confidence < 60):
count = 1
fileOpen = open("face.txt", "r")
for j in fileOpen.readlines():
if (count == ids):
id = str(j[:-1])
confidence = " {0}%".format(round(100 - confidence))
filename=xlwrite.output('attendance','class1',ids,id,'yes');
else:
id = "unknown"
confidence = " {0}%".format(round(100 - confidence))
cv2.putText(img, str(id), (x + 5, y - 5), font, 1, (255, 255, 255), 2)
cv2.putText(img, str(confidence), (x + 5, y + h - 5), font, 1, (255, 255, 0), 1)
cv2.imshow('camera', img)
k = cv2.waitKey(10) & 0xff
if k==27:
break;
if time.time()>start+period:
break;
print("\n [INFO] Exiting Program ")
cam.release()
cv2.destroyAllWindows()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cas.detectMultiScale(gray, 1.3, 7)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + w]
roi_color = img[y:y + h, x:x + w]
eyes = eye_cas.detectMultiScale(roi_gray)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0),
2)
id, conf = recognizer.predict(roi_gray)
if (conf < 60):
if (id == 1):
id = 'Srinivasa'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 1, id,
'yes')
dict[str(id)] = str(id)
elif (id == 2):
id = 'Pavan'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 2, id,
'yes')
dict[str(id)] = str(id)
elif (id == 3):
id = 'Bala'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 3, id,
'yes')
dict[str(id)] = str(id)
cam = cv2.VideoCapture(0)
fontface = cv2.FONT_HERSHEY_SIMPLEX
fontscale = 1
fontcolor = (255, 255, 255)
while True:
ret, im =cam.read()
gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
faces=faceCascade.detectMultiScale(gray, 1.2,5);
for(x,y,w,h) in faces:
cv2.rectangle(im,(x,y),(x+w,y+h),(0,0,255),2)
id, conf = recognizer.predict(gray[y:y+h,x:x+w])
profile=getProfile(id)
if(profile!=None):
if(id==1):
if((str(id)) not in dict):
filename=xlwrite.output('attendance','class1',1,str(profile[1]),'yes');
dict[str(id)]=str(id);
elif(id==2):
if ((str(id)) not in dict):
filename=xlwrite.output('attendance', 'class1', 2, str(profile[1]), 'yes');
dict[str(id)]=str(id);
"""elif(str(profile[0])==3):
if ((str(id)) not in dict):
filename =xlwrite.output('attendance', 'class1', 3, str(profile[1]), 'yes');
dict[str(id)] = str(id);
else:
id="Unknown"""
cv2.putText(im,str(profile[1]),(x,y+h),fontface,fontscale,fontcolor);
cv2.imshow('im',im)
if time.time()>start+period:
def function3():
start = time.time()
period = 8
face_cas = cv2.CascadeClassifier('haarcascade_profileface.xml')
cap = cv2.VideoCapture(0)
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
flag = 0
id = 0
filename = 'filename'
dict = {'item1': 1}
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cas.detectMultiScale(gray)
for (x, y, w, h) in faces:
roi_gray = gray[y:y + h, x:x + w]
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
id, conf = recognizer.predict(roi_gray)
if (conf < 200):
if (id == 1):
id = 'Kunal'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 1,
id, 'P')
dict[str(id)] = str(id)
elif (id == 2):
id = 'Anshu'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 2,
id, 'P')
dict[str(id)] = str(id)
elif (id == 3):
id = 'Divya'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 3,
id, 'P')
dict[str(id)] = str(id)
elif (id == 4):
id = 'AziroAzide'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 4,
id, 'P')
dict[str(id)] = str(id)
else:
id = 'Unrecognized Person ' + str(id)
filename = xlwrite.output('attendance', 'class1', 5, id,
'P')
flag += 1
break
else:
print("Failure in reading!!!!!")
cv2.putText(img,
str(id) + " " + str(conf), (x, y - 10), font, 0.55,
(120, 255, 120), 1)
#cv2.cv.PutText(cv2.cv.fromarray(img),str(id),(x,y+h),font,(0,0,255));
cv2.imshow('frame', img)
#cv2.imshow('gray',gray);
if flag == 10:
print("Transaction Blocked")
break
if time.time() > start + period:
break
if cv2.waitKey(100) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
#font = cv2.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 5, 1, 0, 1, 1)
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cas.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
roi_gray = gray[y:y + h, x:x + w]
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
id, conf = recognizer.predict(roi_gray)
if (id == 1):
id = '1'
name = 'Jannat'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 1, name, id,
'Yes')
dict[str(id)] = str(id)
if (id == 2):
id = '2'
name = 'Asik Syed'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 2, name, id,
'Yes')
dict[str(id)] = str(id)
if (id == 3):
id = '3'
name = 'Mizan'
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 3, name, id,
# For each face in faces
for (x, y, w, h) in faces:
# Create rectangle around the face
cv2.rectangle(im, (x - 20, y - 20), (x + w + 20, y + h + 20),
(0, 255, 0), 4)
# Recognize the face belongs to which ID
Id, confidence = recognizer.predict(gray[y:y + h, x:x + w])
# Check the ID if exist
if (confidence < 50):
if (Id == 1):
Id = "Kshitiz {0:.2f}%".format(round(100 - confidence, 2))
if ((str(Id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 2, Id,
'yes')
dict[str(Id)] = str(Id)
elif (Id == 2):
Id = "Shiv {0:.2f}%".format(round(100 - confidence, 2))
if ((str(Id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 1, Id,
'yes')
dict[str(Id)] = str(Id)
elif (Id == 3):
Id = "Richa {0:.2f}%".format(round(100 - confidence, 2))
if ((str(Id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 3, Id,
'yes')
dict[str(Id)] = str(Id)
}
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
ret, img = cap.read();
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY);
faces = face_cas.detectMultiScale(gray, 1.3, 7);
for (x,y,w,h) in faces:
roi_gray = gray[y:y + h, x:x + w]
cv2.rectangle(img, (x,y), (x+w, y+h), (255,0,0),2);
id,conf=recognizer.predict(roi_gray)
if(id==1):
id='vipin khandelwal'
if((str(id)) not in dict):
filename=xlwrite.output('attendance','class1',1,id,'yes');
dict[str(id)]=str(id);
elif(id==2):
id = 'vivek sharma'
if ((str(id)) not in dict):
filename =xlwrite.output('attendance', 'class1', 2, id, 'yes');
dict[str(id)] = str(id);
cv2.putText(img,str(id)+" "+str(conf),(x,y-10),font,0.55,(120,255,120),1)
cv2.imshow('frame',img);
if time.time()>start+period:
for (x,y,w,h) in faces_detected:
cv2.rectangle(test_img,(x,y),(x+w,y+h),(255,0,0),thickness=4)
resized_img = cv2.resize(test_img, (1000, 700))
cv2.imshow('face detection Tutorial ',resized_img)
cv2.waitKey(10)
for face in faces_detected:
(x,y,w,h)=face
roi_gray=gray_img[y:y+w, x:x+h]
label,confidence=face_recognizer.predict(roi_gray)#predicting the label of given image
#print("confidence:",confidence)
#print("label:",label)
fr.draw_rect(test_img,face)
predicted_name=name[label]
if confidence < 37:#If confidence less than 37 then don't print predicted face text on screen
fr.put_text(test_img,predicted_name,x,y)
resized_img = cv2.resize(test_img, (1000, 700))
cv2.imshow('face recognition tutorial ',resized_img)
if time.time()>start+period:
break;
if cv2.waitKey(100) & 0xFF == ord('q'):
break;
print("label:",name[label])
filename =xlwrite.output('attendance', 'class2', label, name[label], 'yes');
cap.release()
cv2.destroyAllWindows
confidence = int(100 * (1 - (conf) / 300))
print(confidence)
if confidence >= 78:
filt = df['Rollno'] == id
name = df[filt]['Name'].values
Enrollno = df[filt]['Enrollno'].values
Course = df[filt]['Course'].values
Sem = df[filt]['Sem'].values
Section = df[filt]['Section'].values
Contact = df[filt]['Contact'].values
Email = df[filt]['Email'].values
cv2.putText(img,
str(id) + " " + str(conf), (x, y - 10), font, 0.55,
(120, 255, 120), 1)
filename = xlwrite.output('attendance', 'class1', id, name[0],
Enrollno[0], Course[0], Sem[0],
Section[0], Contact[0], Email[0],
'yes')
dict[str(id)] = str(id)
match = 1
match1 = match1 + 1
#if flg==len(faces):
speak('Thanks' + name[0] + 'your attandnce successfully done')
flg = flg + 1
break
else:
cv2.putText(img, "face is not recognize", (x, y - 10), font,
0.55, (120, 255, 120), 1)
speak(
'face is not recognize you are not register please register then try again'
)
else:
if (confidence > 100):
cv2.putText(im, "Unknown", (x, y - 40), font, 1, (255, 255, 255),
3)
else:
cv2.putText(im,
str(Id) + " " + str(round(confidence, 2)) + "%",
(x, y - 40), font, 1, (255, 255, 255), 3)
##for i in range(1, 90):
##filename = xlwrite.output('attendance','class1',i, 16115000 + i, 'no')
for i in range(1, 91):
if ((100 - confidence) < 50 and (100 - confidence) > 0):
if (Id == 16115000 + i):
if ((str(Id)) not in dict):
filename = xlwrite.output('attendance', 'class1', i,
16115000 + i, 'YES')
dict[str(16115000 + i)] = str(16115000 + i)
for i in range(1, 91):
if ((str(16115000 + i)) not in dict):
filename = xlwrite.output('attendance', 'class1', i,
16115000 + i, 'NO')
'''
elif(Id==16115019):
if ((str(Id)) not in dict):
filename =xlwrite.output('attendance', 'class1', 2, Id, 'yes');
dict[str(Id)] = str(Id);
elif(Id==16115004):
if ((str(Id)) not in dict):
filename =xlwrite.output('attendance', 'class1', 3, Id, 'yes');
filename = 'filename'
dict = {'item1': 1}
#font = cv2.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 5, 1, 0, 1, 1)
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cas.detectMultiScale(gray, 1.3, 7)
newtime = datetime.now().time()
for (x, y, w, h) in faces:
roi_gray = gray[y:y + h, x:x + w]
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
id, conf = recognizer.predict(roi_gray)
if (conf < 50):
if ((str(id)) not in dict):
filename = xlwrite.output('attendance', 'class1', 1, id,
newtime)
playsound('thank_you.mp3')
dict[str(id)] = str(id)
else:
time.sleep(3)
playsound('youarepresent.mp3')
else:
id = 'Unknown, can not recognize'
flag = flag + 1
continue
cv2.putText(img,
str(id) + " " + str(conf), (x, y - 10), font, 0.55,
(120, 255, 120), 1)
#cv2.cv.PutText(cv2.cv.fromarray(img),str(id),(x,y+h),font,(0,0,255));
cv2.imshow('frame', img)
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cas.detectMultiScale(gray, 1.3, 7)
print(faces)
for (x, y, w, h) in faces:
roi_gray = gray[y:y + h, x:x + w]
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
id_, conf = recognizer.predict(roi_gray)
print(id_, conf)
if (conf > 100):
if (id_ == 1):
id_ = 'Neeraj Singh'
if ((str(id_)) not in dict_):
print("Neeraj")
filename = xlwrite.output('Attendance', 'class1', 1, id_,
'yes')
dict_[str(id_)] = str(id_)
elif (id_ == 2):
id_ = 'Milind Monam'
if ((str(id_)) not in dict_):
filename = xlwrite.output('Attendance', 'class1', 2, id_,
'yes')
dict_[str(id_)] = str(id_)
elif (id_ == 3):
id_ = 'Mukesh Goyal'
if ((str(id_)) not in dict_):
filename = xlwrite.output('Attendance', 'class1', 3, id_,
'yes')
dict_[str(id_)] = str(id_)
