This code has been taken from github.I have installed all the Dependencies. What could be the possible fix for this issue?
If I try to run this project I get these errors
Traceback (most recent call last):
File "c:\Project\Drowsiness-Detection-System-for-Drivers\driver_drowsiness.py", line 102, in <module>
cv2.imshow("Result of detector", face_frame)
NameError: name 'face_frame' is not defined
[ WARN:[email protected]] global D:\a\opencv-python\opencv-python\opencv\modules\videoio\src\cap_msmf.cpp (539) `anonymous-namespace'::SourceReaderCB::~SourceReaderCB terminating async callback
# Importing OpenCV Library for basic image processing functions
import cv2
# Numpy for array related functions
import numpy as np
# Dlib for deep learning based Modules and face landmark detection
import dlib
# face_utils for basic operations of conversion
from imutils import face_utils
# Initializing the camera and taking the instance
cap = cv2.VideoCapture(0)
# Initializing the face detector and landmark detector
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
# status marking for current state
sleep = 0
drowsy = 0
active = 0
status = ""
color = (0, 0, 0)
def compute(ptA, ptB):
dist = np.linalg.norm(ptA - ptB)
return dist
def blinked(a, b, c, d, e, f):
up = compute(b, d) compute(c, e)
down = compute(a, f)
ratio = up/(2.0*down)
# Checking if it is blinked
if(ratio > 0.25):
return 2
elif(ratio > 0.21 and ratio <= 0.25):
return 1
else:
return 0
while True:
_, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray)
# detected face in faces array
for face in faces:
x1 = face.left()
y1 = face.top()
x2 = face.right()
y2 = face.bottom()
face_frame = frame.copy()
cv2.rectangle(face_frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
landmarks = predictor(gray, face)
landmarks = face_utils.shape_to_np(landmarks)
# The numbers are actually the landmarks which will show eye
left_blink = blinked(landmarks[36], landmarks[37],
landmarks[38], landmarks[41], landmarks[40], landmarks[39])
right_blink = blinked(landmarks[42], landmarks[43],
landmarks[44], landmarks[47], landmarks[46], landmarks[45])
# Now judge what to do for the eye blinks
if(left_blink == 0 or right_blink == 0):
sleep = 1
drowsy = 0
active = 0
if(sleep > 6):
status = "SLEEPING !!!"
color = (255, 0, 0)
elif(left_blink == 1 or right_blink == 1):
sleep = 0
active = 0
drowsy = 1
if(drowsy > 6):
status = "Drowsy !"
color = (0, 0, 255)
else:
drowsy = 0
sleep = 0
active = 1
if(active > 6):
status = "Active :)"
color = (0, 255, 0)
cv2.putText(frame, status, (100, 100),
cv2.FONT_HERSHEY_SIMPLEX, 1.2, color, 3)
for n in range(0, 68):
(x, y) = landmarks[n]
cv2.circle(face_frame, (x, y), 1, (255, 255, 255), -1)
cv2.imshow("Frame", frame)
cv2.imshow("Result of detector", face_frame)
key = cv2.waitKey(1)
if key == 27:
break
CodePudding user response：
There is an issue in the module itself for face_frame variable usage, which is already reported in the github reported issue for face_frame
Working Code:-
# Importing OpenCV Library for basic image processing functions
import cv2
# Numpy for array related functions
import numpy as np
# Dlib for deep learning based Modules and face landmark detection
import dlib
# face_utils for basic operations of conversion
from imutils import face_utils
# Initializing the camera and taking the instance
cap = cv2.VideoCapture(0)
# Initializing the face detector and landmark detector
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
# status marking for current state
sleep = 0
drowsy = 0
active = 0
status = ""
color = (0, 0, 0)
def compute(ptA, ptB):
dist = np.linalg.norm(ptA - ptB)
return dist
def blinked(a, b, c, d, e, f):
up = compute(b, d) compute(c, e)
down = compute(a, f)
ratio = up/(2.0*down)
# Checking if it is blinked
if(ratio > 0.25):
return 2
elif(ratio > 0.21 and ratio <= 0.25):
return 1
else:
return 0
while True:
_, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray)
face_frame = frame.copy()
# detected face in faces array
for face in faces:
x1 = face.left()
y1 = face.top()
x2 = face.right()
y2 = face.bottom()
cv2.rectangle(face_frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
landmarks = predictor(gray, face)
landmarks = face_utils.shape_to_np(landmarks)
# The numbers are actually the landmarks which will show eye
left_blink = blinked(landmarks[36], landmarks[37],
landmarks[38], landmarks[41], landmarks[40], landmarks[39])
right_blink = blinked(landmarks[42], landmarks[43],
landmarks[44], landmarks[47], landmarks[46], landmarks[45])
# Now judge what to do for the eye blinks
if(left_blink == 0 or right_blink == 0):
sleep = 1
drowsy = 0
active = 0
if(sleep > 6):
status = "SLEEPING !!!"
color = (255, 0, 0)
elif(left_blink == 1 or right_blink == 1):
sleep = 0
active = 0
drowsy = 1
if(drowsy > 6):
status = "Drowsy !"
color = (0, 0, 255)
else:
drowsy = 0
sleep = 0
active = 1
if(active > 6):
status = "Active :)"
color = (0, 255, 0)
cv2.putText(frame, status, (100, 100),
cv2.FONT_HERSHEY_SIMPLEX, 1.2, color, 3)
for n in range(0, 68):
(x, y) = landmarks[n]
cv2.circle(face_frame, (x, y), 1, (255, 255, 255), -1)
cv2.imshow("Frame", frame)
cv2.imshow("Result of detector", face_frame)
key = cv2.waitKey(1)
if key == 27:
break