April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How to do it...
Perform the following steps to implement face detection with pretrained Haar-Cascade classifiers with opencv-python:
- First, load the pretrained classifiers to detect the face, eyes, and smile, respectively, from the corresponding xml files:
face_cascade = cv2.CascadeClassifier('models/haarcascade_frontalface_alt2.xml')eye_cascade = cv2.CascadeClassifier('models/haarcascade_eye.xml') #haarcascade_eye_tree_eyeglasses.xmlsmile_cascade = cv2.CascadeClassifier('models/face_detect/haarcascade_smile.xml')
- Read the input image (containing seven faces) and convert it into grayscale. Detect the faces present in the image using the face cascade classifier model:
img = cv2.imread('images/all.png')gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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