File size: 2,918 Bytes
3bbb319 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | # -*- 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
|