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# code was heavily based on https://github.com/wtjiang98/PSGAN
# MIT License
# Copyright (c) 2020 Wentao Jiang
import os
import os.path as osp
import numpy as np
from PIL import Image
from paddle.utils import try_import
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):
dlib = try_import('dlib')
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):
dlib = try_import('dlib')
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):
dlib = try_import('dlib')
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):
dlib = try_import('dlib')
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):
dlib = try_import('dlib')
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