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Face detect and crop by using OpenCV
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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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