I am currently creating a django face detection/recognition app to mark employee attendance, however I am facing some issues when capturing the camera feed and detecting the faces on the feed.
The functions below within the view.py are to detect the employee face and capture 300 images of the logged in employee - Essentially the aim of this question is to resolve the face detection issue and the issue is specifically lying within face_aligned = fa.align(frame, gray_frame, face).
views.py:
def create_dataset(username):
id = username
if (os.path.exists('Recog_Data/Train_Data/{}/'.format(id)) == False):
os.makedirs('Recog_Data/Train_Data/{}/'.format(id))
directory = 'Recog_Data/Train_Data/{}/'.format(id)
# Detect face
# Loading the HOG face detector and the shape predictpr for allignment
print("[INFO] Loading the facial detector")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('Recog_Data/shape_predictor_68_face_landmarks.dat') # Add path to the shape predictor ######CHANGE TO RELATIVE PATH LATER
fa = FaceAligner(predictor, desiredFaceWidth=256)
# capture images from the webcam and process and detect the face
# Initialize the video stream
print("[INFO] Initializing Video stream")
vs = VideoStream(src=0).start()
# time.sleep(2.0) ####CHECK######
# Our identifier
# We will put the id here and we will store the id with a face, so that later we can identify whose face it is
# Our dataset naming counter
sampleNum = 0
# Capturing the faces one by one and detect the faces and showing it on the window
while (True):
# Capturing the image
# vs.read each frame
frame = vs.read()
# Resize each image
frame = imutils.resize(frame, width=800)
# the returned img is a colored image but for the classifier to work we need a greyscale image
# to convert
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# To store the faces
# This will detect all the images in the current frame, and it will return the coordinates of the faces
# Takes in image and some other parameter for accurate result
faces = detector(gray_frame, 2)
# In above 'faces' variable there can be multiple faces so we have to get each and every face and draw a rectangle around it.
for face in faces:
print("inside for loop")
(x, y, w, h) = face_utils.rect_to_bb(face)
face_aligned = fa.align(frame, gray_frame, face)
# Whenever the program captures the face, we will write that is a folder
# Before capturing the face, we need to tell the script whose face it is
# For that we will need an identifier, here we call it id
# So now we captured a face, we need to write it in a file
sampleNum = sampleNum + 1
# Saving the image dataset, but only the face part, cropping the rest
if face is None:
print("face is none")
continue
cv2.imwrite(directory + '/' + str(sampleNum) + '.jpg', face_aligned)
face_aligned = imutils.resize(face_aligned, width=400)
# cv2.imshow("Image Captured",face_aligned)
# @params the initial point of the rectangle will be x,y and
# @params end point will be x+width and y+height
# @params along with color of the rectangle
# @params thickness of the rectangle
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 1)
# Before continuing to the next loop, I want to give it a little pause
# waitKey of 100 millisecond
cv2.waitKey(50)
# Showing the image in another window
# Creates a window with window name "Face" and with the image img
cv2.imshow("Add Images", frame)
# Before closing it we need to give a wait command, otherwise the open cv wont work
# @params with the millisecond of delay 1
cv2.waitKey(1)
# To get out of the loop
if (sampleNum > 300):
break
# Stoping the videostream
vs.stop()
# destroying all the windows
cv2.destroyAllWindows()
@login_required
def add_photos(request):
if not request.user.is_authenticated:
messages.warning(request, f'Employee not authorised')
return redirect('dashboard')
elif request.user.is_authenticated:
user = request.user
create_dataset(user)
messages.success(request, f'Dataset Created')
return redirect('dashboard')
else:
messages.warning(request, f'Error: dataset not created')
return render(request, 'dashboard')
The stacktrace related to the error:
Traceback (most recent call last):
File "/Users/xxxx/Desktop/djangoWebcamTest/venv/lib/python3.9/site-packages/django/core/handlers/exception.py", line 47, in inner
response = get_response(request)
File "/Users/xxxx/Desktop/djangoWebcamTest/venv/lib/python3.9/site-packages/django/core/handlers/base.py", line 181, in _get_response
response = wrapped_callback(request, *callback_args, **callback_kwargs)
File "/Users/xxxx/Desktop/djangoWebcamTest/venv/lib/python3.9/site-packages/django/contrib/auth/decorators.py", line 21, in _wrapped_view
return view_func(request, *args, **kwargs)
File "/Users/xxxx/Desktop/djangoWebcamTest/users/views.py", line 204, in add_photos
create_dataset(user)
File "/Users/xxxx/Desktop/djangoWebcamTest/users/views.py", line 157, in create_dataset
face_aligned = fa.align(frame, gray_frame, face)
File "/Users/xxxx/Desktop/djangoWebcamTest/venv/lib/python3.9/site-packages/imutils/face_utils/facealigner.py", line 68, in align
M = cv2.getRotationMatrix2D(eyesCenter, angle, scale)
Exception Type: TypeError at /vidstream/
Exception Value: Can't parse 'center'. Sequence item with index 0 has a wrong type
This is a screenshot of the variables being printed to console - face_aligned = fa.align(frame, gray_frame, face):
Any help with this issue would be greatly appreciated
