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Face detect and crop by using OpenCV
import cv2
import sys
import os
class FaceCropper(object):
CASCADE_PATH = "data/haarcascades/haarcascade_frontalface_default.xml"
def __init__(self):
self.face_cascade = cv2.CascadeClassifier(self.CASCADE_PATH)
def generate(self, image_path, show_result):
img = cv2.imread(image_path)
if (img is None):
print("Can't open image file")
return 0
#img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = self.face_cascade.detectMultiScale(img, 1.1, 3, minSize=(100, 100))
if (faces is None):
print('Failed to detect face')
return 0
if (show_result):
for (x, y, w, h) in faces:
cv2.rectangle(img, (x,y), (x+w, y+h), (255,0,0), 2)
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
facecnt = len(faces)
print("Detected faces: %d" % facecnt)
i = 0
height, width = img.shape[:2]
for (x, y, w, h) in faces:
r = max(w, h) / 2
centerx = x + w / 2
centery = y + h / 2
nx = int(centerx - r)
ny = int(centery - r)
nr = int(r * 2)
faceimg = img[ny:ny+nr, nx:nx+nr]
lastimg = cv2.resize(faceimg, (32, 32))
i += 1
cv2.imwrite("image%d.jpg" % i, lastimg)
if __name__ == '__main__':
args = sys.argv
argc = len(args)
if (argc != 2):
print('Usage: %s [image file]' % args[0])
quit()
detecter = FaceCropper()
detecter.generate(args[1], True)
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