import numpy as np
import cv2


def crop_face(img, lmk_extractor, expand=1.5):
    print('****=====1======')
    result = lmk_extractor(img)  # cv2 BGR
    
    print('****=====2======')

    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