Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
#import required libraries
import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt
%matplotlib inline
#load the classifiers downloaded
face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv.CascadeClassifier('haarcascade_eye.xml')
#read the image and convert to grayscale format
img = cv.imread('rotated_face.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
#calculate coordinates
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
for (x,y,w,h) in faces:
cv.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)
#draw bounding boxes around detected features
for (ex,ey,ew,eh) in eyes:
cv.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
#plot the image
plt.imshow(img)
#write image
cv2.imwrite('face_detection.jpg',img)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.