# -*- coding: utf-8 -*-

# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2022 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Contact: mica@tue.mpg.de


import os
import os.path as osp
from pathlib import Path

import cv2
import numpy as np
from insightface.utils import face_align
from numpy.lib import math

input_mean = 127.5
input_std = 127.5


def create_folders(folders):
    if not type(folders) is list:
        folders = folders.split('/')
    parents = '/'
    for folder in folders:
        parents = os.path.join(parents, folder)
        if os.path.exists(parents):
            continue
        Path(parents).mkdir(exist_ok=True)


def get_arcface_input(face, img):
    aimg = face_align.norm_crop(img, landmark=face.kps)
    blob = cv2.dnn.blobFromImages([aimg], 1.0 / input_std, (112, 112), (input_mean, input_mean, input_mean), swapRB=True)
    return blob[0], aimg


def get_image(name, to_rgb=False):
    images_dir = osp.join(Path(__file__).parent.absolute(), '../images')
    ext_names = ['.jpg', '.png', '.jpeg']
    image_file = None
    for ext_name in ext_names:
        _image_file = osp.join(images_dir, "%s%s" % (name, ext_name))
        if osp.exists(_image_file):
            image_file = _image_file
            break
    assert image_file is not None, '%s not found' % name
    img = cv2.imread(image_file)
    if to_rgb:
        img = img[:, :, ::-1]
    return img


def dist(p1, p2):
    return math.sqrt(((p1[0] - p2[0]) ** 2) + ((p1[1] - p2[1]) ** 2))


def get_center(bboxes, img):
    img_center = img.shape[0] // 2, img.shape[1] // 2
    size = bboxes.shape[0]
    distance = np.Inf
    j = 0
    for i in range(size):
        x1, y1, x2, y2 = bboxes[i, 0:4]
        dx = abs(x2 - x1) / 2.0
        dy = abs(y2 - y1) / 2.0
        current = dist((x1 + dx, y1 + dy), img_center)
        if current < distance:
            distance = current
            j = i

    return j


def bbox2point(left, right, top, bottom, type='bbox'):
    if type == 'kpt68':
        old_size = (right - left + bottom - top) / 2 * 1.1
        center = np.array([right - (right - left) / 2.0, bottom - (bottom - top) / 2.0])
    elif type == 'bbox':
        old_size = (right - left + bottom - top) / 2
        center = np.array([right - (right - left) / 2.0, bottom - (bottom - top) / 2.0 + old_size * 0.12])
    else:
        raise NotImplementedError
    return old_size, center