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AttributeError: module 'cv2' has no attribute 'CascadeClassifier'

im using cv2 to try to take a picture here is my code
import numpy as np
import cv2
face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
eye_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while(True):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)
for (x, y, w, h) in faces:
#print(x,y,w,h)
roi_gray = gray[y:y+h, x:x+w]
roi_color = frame[y:y+h, x:x+w]
img_item = "my-image.png"
cv2.imwrite(img_item, roi_color)
stroke = 2
color = (0, 255, 0)
end_cord_x = x + w
end_cord_y = y + h
ecolor = (50, 50, 50)
cv2.rectangle(frame, (x,y), (end_cord_x, end_cord_y), color, stroke)
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex,ey), (ex+ew,ey+eh), ecolor, 1)
cv2.imshow('frame',frame)
if cv2.waitKey(20) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
i get the error:
File "c:NothereForPrivacyReasons\imagerecognition\face\picture.py", line 3, in
face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
AttributeError: module 'cv2' has no attribute 'CascadeClassifier'

How to Extract Faces from a Video Using Haarcascade?

I am using below script for haarcascade face detection.
My aim is to collect face shots on a video.
I would like to extract faces from a video.
Below script provides the detection of faces on a video.
How could I extract detected faces on a video?
import numpy as np
import cv2
#https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_eye.xml
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()

How to show live video feed using opencv?

While attempting to do a facial detection which displays coordinates and their average using Raspberry Pi 3, PiCamera live video stream only shows a static image, whereas I am trying to get live video feed.
vs = VideoStream(usePiCamera=True).start()
time.sleep(2.0)
while True:
frame = vs.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.3, 5)
detected = False
xcoords.clear()
for (x, y, w, h) in faces:
detected= True
cv2.rectangle(frame, (x, y), (x+w,y+h), (255,0,0), 2)
coordinates = (x)
roi_gray = gray[y:y+h, x:x+w]
roi_color = frame[y:y+h, x:x+w]
eyes = eyeCascade.detectMultiScale(roi_gray)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex,ey), (ex+ew,ey+eh), (0,255,0), 2)
cv2.imshow('Frame', frame)
k = cv2.waitKey(0) & 0xff
if k == 27:
break
vs.stop()
cv2.destroyAllWindows()
Does anyone have a solution ?

change k = cv2.waitKey(0) & 0xff to k = cv2.waitKey(1) & 0xff

OpenCV 3.4.0.12 with Python3.5 AttributeError: 'cv2.VideoCapture' object has no attribute 'imread'

I'm trying out facial recognition for the first time with python 3.5 and OpenCV 3.4.0.12 and I get this error when I run my code.
File "/Users/connorwoodford/anaconda3/envs/chatbot/lib/python3.5/site-packages/spyder/utils/site/sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "/Users/connorwoodford/Desktop/temp.py", line 11, in <module>
ret, img = cap.imread()
AttributeError: 'cv2.VideoCapture' object has no attribute 'imread'
Code:
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('CascadeClassifier')
cap = cv2.VideoCapture(0)
while True:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex+ew,ey+eh), (0,255,0), 2)
cv2.imshow('img',img)
k = cv2.waitkey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()

Your eye_cascade is referring to wrong cascade file, it should end with .xml extension. You can download it from here haarcascade_eye.xml.
Also note that your call to cv2.rectangle is not in correct format.
change it from
cv2.rectangle(img, (x+y), (x+w, y+h), (255,0,0), 2)
to
cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)
All you need to make this work is to wrap the capture logic in a method. Full code goes as follows:
import numpy as np
import cv2
def sample_demo():
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
and simply call method sample_demo()
sample_demo()

Viola-Jones in Python with openCV, detection mouth and nose

I have an algorithm Viola-Jones in Python. I'm using haarcascade xml, which I load from openCV root file. But there wasn't any xml file for mouth and nose in openCV, so I downloaded these files from EmguCV. Result for detection of face is OK, but detection of eye isn't good and nose with mouth is very bad. I tried to change parameters in face_cascade.detectMultiScale, but it didn't help at all.
My code:
import cv2
import sys
def facedet(img):
face_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_eye.xml')
mouth_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_mcs_mouth.xml')
nose_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_mcs_nose.xml')
img = cv2.imread(img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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_cascade.detectMultiScale(roi_gray)
nose = nose_cascade.detectMultiScale(roi_gray)
mouth = mouth_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color, (ex,ey), (ex+ew, ey+eh), (0,255,0), 2)
for (nx, ny, nw, nh) in nose:
cv2.rectangle(roi_color, (nx, ny), (nx + nw, ny + nh), (0, 0, 255), 2)
for (mx, my, mw, mh) in mouth:
cv2.rectangle(roi_color, (mx, my), (mx + mw, my + mh), (0, 0, 0), 2)
cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == '__main__':
#img = sys.argv[1]
facedet(img)
My question
What am I doing wrong? Is there any simple solution, which will give me a better result?
Output:

Haar cascades perform alright for faces but not so well for smaller individual parts. A better solution is to detect all the face landmarks together. A good algorithm for that is "One Millisecond Face Alignment with an Ensemble of Regression Trees by Vahid Kazemi and Josephine Sullivan, CVPR 2014" which is implemented in Dlib (http://dlib.net/face_landmark_detection.py.html).

This works really well for me.
I found that if you divide the face into 2 sections and have the eyes look for eyes in the top section, and the mouth in the lower section it works really well.
face
--------
| eyes |
|------|
|mouth |
--------
This is a rough illustration of what I did with the code below.
I am aware the the cascade i use is smile, but the mouth doesn't seem to work.
import cv2
import sys
mouthCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_smile.xml')
faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
eyeCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
video_capture = cv2.VideoCapture(0)
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
mouth = mouthCascade.detectMultiScale(gray, 1.3, 5)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30)
)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
# Draw a rectangle around the faces
roi_gray_mouth = gray[y+(int(h/2)):y+h, x:x+w]
roi_color_mouth = frame[y+(int(h/2)):y+h, x:x+w]
roi_gray_eye = gray[y-(int(h/2)):y+h, x:x+w]
roi_color_eye = frame[y-(int(h/2)):y+h, x:x+w]
mouth = mouthCascade.detectMultiScale(roi_gray_mouth)
eyes = eyeCascade.detectMultiScale(roi_gray_eye)
for (ex,ey,ew,eh) in mouth:
cv2.rectangle(roi_color_mouth, (ex, ey), (ex+ew, ey+eh), (0, 255, 0), 2)
for (eex,eey,eew,eeh) in eyes:
d = int(eew / 2)
cv2.circle(roi_color_eye, (int(eex + eew / 4) + int(d / 2), int(eey + eeh / 4) + int(d / 2)), int(d) ,(0,0,255),2)
# Display the resulting frame
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()

import cv2
import sys
face_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_eye.xml')
mouth_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_mcs_mouth.xml')
nose_cascade = cv2.CascadeClassifier('/home/kattynka/opencv/data/haarcascades/haarcascade_mcs_nose.xml')
img = cv2.imread(img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
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_cascade.detectMultiScale(gray, 1.3, 5)
nose = nose_cascade.detectMultiScale(gray, 1.3, 5)
mouth = mouth_cascade.detectMultiScale(gray, 1.7, 11)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(img, (ex,ey), (ex+ew, ey+eh), (0,255,0), 2)
for (nx, ny, nw, nh) in nose:
cv2.rectangle(img, (nx, ny), (nx + nw, ny + nh), (0, 0, 255), 2)
for (mx, my, mw, mh) in mouth:
cv2.rectangle(img, (mx, my), (mx + mw, my + mh), (0, 0, 0), 2)
cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
you can try this code. It worked for me.