# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import os.path as osp import numpy as np from PIL import Image import dlib import cv2 from ..image import resize_by_max from paddle.utils.download import get_weights_path_from_url LANDMARKS_WEIGHT_URL = 'https://paddlegan.bj.bcebos.com/models/lms.dat' def detect(image: Image): image = np.asarray(image) h, w = image.shape[:2] image = resize_by_max(image, 361) actual_h, actual_w = image.shape[:2] detector = dlib.get_frontal_face_detector() faces_on_small = detector(image, 1) faces = dlib.rectangles() for face in faces_on_small: faces.append( dlib.rectangle(int(face.left() / actual_w * w + 0.5), int(face.top() / actual_h * h + 0.5), int(face.right() / actual_w * w + 0.5), int(face.bottom() / actual_h * h + 0.5))) return faces def crop(image: Image, face, up_ratio, down_ratio, width_ratio): width, height = image.size face_height = face.height() face_width = face.width() delta_up = up_ratio * face_height delta_down = down_ratio * face_height delta_width = width_ratio * width img_left = int(max(0, face.left() - delta_width)) img_top = int(max(0, face.top() - delta_up)) img_right = int(min(width, face.right() + delta_width)) img_bottom = int(min(height, face.bottom() + delta_down)) image = image.crop((img_left, img_top, img_right, img_bottom)) face = dlib.rectangle(face.left() - img_left, face.top() - img_top, face.right() - img_left, face.bottom() - img_top) face_expand = dlib.rectangle(img_left, img_top, img_right, img_bottom) center = face_expand.center() width, height = image.size crop_left = img_left crop_top = img_top crop_right = img_right crop_bottom = img_bottom if width > height: left = int(center.x - height / 2) right = int(center.x + height / 2) if left < 0: left, right = 0, height elif right > width: left, right = width - height, width image = image.crop((left, 0, right, height)) face = dlib.rectangle(face.left() - left, face.top(), face.right() - left, face.bottom()) crop_left += left crop_right = crop_left + height elif width < height: top = int(center.y - width / 2) bottom = int(center.y + width / 2) if top < 0: top, bottom = 0, width elif bottom > height: top, bottom = height - width, height image = image.crop((0, top, width, bottom)) face = dlib.rectangle(face.left(), face.top() - top, face.right(), face.bottom() - top) crop_top += top crop_bottom = crop_top + width crop_face = dlib.rectangle(crop_left, crop_top, crop_right, crop_bottom) return image, face, crop_face def crop_by_image_size(image: Image, face): center = face.center() width, height = image.size if width > height: left = int(center.x - height / 2) right = int(center.x + height / 2) if left < 0: left, right = 0, height elif right > width: left, right = width - height, width image = image.crop((left, 0, right, height)) face = dlib.rectangle(face.left() - left, face.top(), face.right() - left, face.bottom()) elif width < height: top = int(center.y - width / 2) bottom = int(center.y + width / 2) if top < 0: top, bottom = 0, width elif bottom > height: top, bottom = height - width, height image = image.crop((0, top, width, bottom)) face = dlib.rectangle(face.left(), face.top() - top, face.right(), face.bottom() - top) return image, face def landmarks(image: Image, face): weight_path = get_weights_path_from_url(LANDMARKS_WEIGHT_URL) predictor = dlib.shape_predictor(weight_path) shape = predictor(np.asarray(image), face).parts() return np.array([[p.y, p.x] for p in shape]) def crop_from_array(image: np.array, face): ratio = 0.20 / 0.85 # delta_size / face_size height, width = image.shape[:2] face_height = face.height() face_width = face.width() delta_height = ratio * face_height delta_width = ratio * width img_left = int(max(0, face.left() - delta_width)) img_top = int(max(0, face.top() - delta_height)) img_right = int(min(width, face.right() + delta_width)) img_bottom = int(min(height, face.bottom() + delta_height)) image = image[img_top:img_bottom, img_left:img_right] face = dlib.rectangle(face.left() - img_left, face.top() - img_top, face.right() - img_left, face.bottom() - img_top) center = face.center() height, width = image.shape[:2] if width > height: left = int(center.x - height / 2) right = int(center.x + height / 2) if left < 0: left, right = 0, height elif right > width: left, right = width - height, width image = image[0:height, left:right] face = dlib.rectangle(face.left() - left, face.top(), face.right() - left, face.bottom()) elif width < height: top = int(center.y - width / 2) bottom = int(center.y + width / 2) if top < 0: top, bottom = 0, width elif bottom > height: top, bottom = height - width, height image = image[top:bottom, 0:width] face = dlib.rectangle(face.left(), face.top() - top, face.right(), face.bottom() - top) return image, face