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import traceback
import cv2
import numpy as np
from modules import images
from PIL import Image
from scripts.reactor_entities.rect import Point, Rect
class FaceArea:
def __init__(self, entire_image: np.ndarray, face_area: Rect, face_margin: float, face_size: int, upscaler: str):
self.face_area = face_area
self.center = face_area.center
left, top, right, bottom = face_area.to_square()
self.left, self.top, self.right, self.bottom = self.__ensure_margin(
left, top, right, bottom, entire_image, face_margin
)
self.width = self.right - self.left
self.height = self.bottom - self.top
self.image = self.__crop_face_image(entire_image, face_size, upscaler)
self.face_size = face_size
self.scale_factor = face_size / self.width
self.face_area_on_image = self.__get_face_area_on_image()
self.landmarks_on_image = self.__get_landmarks_on_image()
def __get_face_area_on_image(self):
left = int((self.face_area.left - self.left) * self.scale_factor)
top = int((self.face_area.top - self.top) * self.scale_factor)
right = int((self.face_area.right - self.left) * self.scale_factor)
bottom = int((self.face_area.bottom - self.top) * self.scale_factor)
return self.__clip_values(left, top, right, bottom)
def __get_landmarks_on_image(self):
landmarks = []
if self.face_area.landmarks is not None:
for landmark in self.face_area.landmarks:
landmarks.append(
Point(
int((landmark.x - self.left) * self.scale_factor),
int((landmark.y - self.top) * self.scale_factor),
)
)
return landmarks
def __crop_face_image(self, entire_image: np.ndarray, face_size: int, upscaler: str):
cropped = entire_image[self.top : self.bottom, self.left : self.right, :]
if upscaler:
return images.resize_image(0, Image.fromarray(cropped), face_size, face_size, upscaler)
else:
return Image.fromarray(cv2.resize(cropped, dsize=(face_size, face_size)))
def __ensure_margin(self, left: int, top: int, right: int, bottom: int, entire_image: np.ndarray, margin: float):
entire_height, entire_width = entire_image.shape[:2]
side_length = right - left
margin = min(min(entire_height, entire_width) / side_length, margin)
diff = int((side_length * margin - side_length) / 2)
top = top - diff
bottom = bottom + diff
left = left - diff
right = right + diff
if top < 0:
bottom = bottom - top
top = 0
if left < 0:
right = right - left
left = 0
if bottom > entire_height:
top = top - (bottom - entire_height)
bottom = entire_height
if right > entire_width:
left = left - (right - entire_width)
right = entire_width
return left, top, right, bottom
def get_angle(self) -> float:
landmarks = getattr(self.face_area, "landmarks", None)
if landmarks is None:
return 0
eye1 = getattr(landmarks, "eye1", None)
eye2 = getattr(landmarks, "eye2", None)
if eye2 is None or eye1 is None:
return 0
try:
dx = eye2.x - eye1.x
dy = eye2.y - eye1.y
if dx == 0:
dx = 1
angle = np.arctan(dy / dx) * 180 / np.pi
if dx < 0:
angle = (angle + 180) % 360
return angle
except Exception:
print(traceback.format_exc())
return 0
def rotate_face_area_on_image(self, angle: float):
center = [
(self.face_area_on_image[0] + self.face_area_on_image[2]) / 2,
(self.face_area_on_image[1] + self.face_area_on_image[3]) / 2,
]
points = [
[self.face_area_on_image[0], self.face_area_on_image[1]],
[self.face_area_on_image[2], self.face_area_on_image[3]],
]
angle = np.radians(angle)
rot_matrix = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]])
points = np.array(points) - center
points = np.dot(points, rot_matrix.T)
points += center
left, top, right, bottom = (int(points[0][0]), int(points[0][1]), int(points[1][0]), int(points[1][1]))
left, right = (right, left) if left > right else (left, right)
top, bottom = (bottom, top) if top > bottom else (top, bottom)
width, height = right - left, bottom - top
if width < height:
left, right = left - (height - width) // 2, right + (height - width) // 2
elif height < width:
top, bottom = top - (width - height) // 2, bottom + (width - height) // 2
return self.__clip_values(left, top, right, bottom)
def __clip_values(self, *args):
result = []
for val in args:
if val < 0:
result.append(0)
elif val > self.face_size:
result.append(self.face_size)
else:
result.append(val)
return tuple(result)
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