Example for Face detection a Addition to the post Face recognition with OpenCV and the Viola-Jones algorithm

befor you beginn download on https://github.com/opencv/opencv/tree/master/data/haarcascades this files:

haarcascade_frontalface_default.xml
haarcascade_eye.xml
haarcascade_smile.xml

and put it in a directory called cascade_classifier

Next copy from site the 3 images and take it in a directory with name images

Once you have downloaded all the files, install the following with pip:

pip install numpy
pip install pandas
pip install matplotlib
pip install jupyter
pip install pillow
pip install opencv-python
pip install sklearn

import numpy as np
import cv2

Face Detection

img = cv2.imread('./images/0021.jpg')

cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

# Load cascassde classifire - frontalface
face_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_frontalface_default.xml')

# apply cascade classfier to an image
faces, num_detection = face_cascade.detectMultiScale2(img)

print(faces)

[[114 40 196 196]]

print(num_detection)

[89]

next var:

pt1 = (114,40)
pt2= (114+196, 40+196)

draw the rectangle

cv2.rectangle(img, pt1, pt2, (0,255,0))

cv2.imshow('face detection', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

draw the circle

cx = 114 + 196 //2
cy = 40 + 196 //2
r = 196 //2

cv2.circle(img,(cx,cy),r, (0,255,255) )

cv2.imshow('face detection', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Multiple Face Detection

img = cv2.imread('./images/friends.jpg')

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

# step 1: apply cascade classfier to an image
faces, num_detection = face_cascade.detectMultiScale2(img, minNeighbors=8)

#step2: run a loop
for x,y,w,h in faces:
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0))
    
# step 3: display the image

cv2.imshow('face detection rectangle', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Faces & Eyes Dection

img = cv2.imread('./images/friends.jpg')

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

face_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_eye.xml')

# step 1: Face detection
faces, num_detection = face_cascade.detectMultiScale2(img, minNeighbors=8)
for x,y,w,h in faces:
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0))
    
    # setp 2: croping the face
    face_roi = img[y:y+h, x:x+h] # croping the image
    # step 3: apply cascade classfier (eye)
    eyes, num_detection_eyes = faces, num_detection = eye_cascade.detectMultiScale2(face_roi)
    for ex, ey, ew, eh in eyes:
        cx = x + ex + ew //2
        cy = y + ey + eh //2
        r = eh //2
        cv2.circle(img,(cx,cy),r, (0,255,255),2)
        
# step 4:
cv2.imshow('face eye detection', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Faces, Eyes, Smiles Detection

img = cv2.imread('./images/friends.jpg')

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

face_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_eye.xml')
smile_cascade = cv2.CascadeClassifier('./cascade_classifier/haarcascade_smile.xml')

faces, num_detection = face_cascade.detectMultiScale2(img, minNeighbors=8)
for x,y,w,h in faces:
    face_roi = img[y:y+h, x:x+h].copy() # croping the image
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0))
        
    # step 2: apply cascade classfier (eye)
    eyes, num_detection_eyes = eye_cascade.detectMultiScale2(face_roi)
    for ex, ey, ew, eh in eyes:
        cx = x + ex + ew //2
        cy = y + ey + eh //2
        r = eh //2
        cv2.circle(img,(cx,cy),r, (0,255,255),2)
        
    # step 3: smile detection
    smiles, num_detection_smile = smile_cascade.detectMultiScale2(face_roi)
    for sx, sy, sw, sh in smiles:
        cv2.rectangle(img,(x+sx,y+sy),(x+sx+sw, y+sy+sh),(255,0,0),2)
        
# step 4:
cv2.imshow('face eye detection', img)
cv2.waitKey(0)
cv2.destroyAllWindows()