# это файл из ветки stylegan
from dataloaders.voxceleb2_segmentation_nolandmarks import bbox_to_integer_coords, crop_with_padding

import cv2
import dlib
face_detector = dlib.get_frontal_face_detector()

def crop_as_in_voxceleb1(image):
    """
        image:
            np.uint8, (H x W x 3)

        return:
            np.uint8, (256 x 256 x 3)
    """
    bboxes = self.face_detector(image)
    if bboxes:
        bbox = bboxes[0]
        l_dlib, t_dlib, r_dlib, b_dlib = bbox.left(), bbox.top(), bbox.right(), bbox.bottom()

        center_x = (l_dlib + r_dlib) * 0.5
        center_y = (t_dlib + b_dlib) * 0.5
        size = r_dlib - l_dlib
        new_size = size * 1.672
        l_dlib, r_dlib = round(center_x-new_size/2), round(center_x+new_size/2+1)
        t_dlib, b_dlib = round(center_y-new_size/2), round(center_y+new_size/2+1)
    else:
        l, t, r, b = 0, 0, 1.0, 1.0

        # Make bbox square and scale it
        SCALE = 0.7083

        center_x, center_y = (l + r) * 0.5, (t + b) * 0.5
        height, width = b - t, r - l
        new_box_size = max(height, width)
        l = center_x - new_box_size / 2 * SCALE
        r = center_x + new_box_size / 2 * SCALE
        t = center_y - new_box_size / 2 * SCALE
        b = center_y + new_box_size / 2 * SCALE

        l_dlib, t_dlib, r_dlib, b_dlib = bbox_to_integer_coords(t, l, b, r, *image.shape[:2])

    image_cropped_voxceleb = crop_with_padding(image, t_dlib, l_dlib, b_dlib, r_dlib)
    image_cropped_voxceleb = cv2.resize(image_cropped_voxceleb, (256, 256),
        interpolation=cv2.INTER_CUBIC if 256 > b_dlib - r_dlib else cv2.INTER_AREA)