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import numpy as np
import cv2
def crop_face(img, lmk_extractor, expand=1.5):
result = lmk_extractor(img) # cv2 BGR
if result is None:
return None
H, W, _ = img.shape
lmks = result['lmks']
lmks[:, 0] *= W
lmks[:, 1] *= H
x_min = np.min(lmks[:, 0])
x_max = np.max(lmks[:, 0])
y_min = np.min(lmks[:, 1])
y_max = np.max(lmks[:, 1])
width = x_max - x_min
height = y_max - y_min
if width*height >= W*H*0.15:
if W == H:
return img
size = min(H, W)
offset = int((max(H, W) - size)/2)
if size == H:
return img[:, offset:-offset]
else:
return img[offset:-offset, :]
else:
center_x = x_min + width / 2
center_y = y_min + height / 2
width *= expand
height *= expand
size = max(width, height)
x_min = int(center_x - size / 2)
x_max = int(center_x + size / 2)
y_min = int(center_y - size / 2)
y_max = int(center_y + size / 2)
top = max(0, -y_min)
bottom = max(0, y_max - img.shape[0])
left = max(0, -x_min)
right = max(0, x_max - img.shape[1])
img = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, value=0)
cropped_img = img[y_min + top:y_max + top, x_min + left:x_max + left]
return cropped_img
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