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| from math import dist | |
| import cv2 | |
| import mediapipe as mp | |
| from points import points | |
| from ratios import Ratios | |
| from utils import * | |
| def convert_to_numpy_array(ratios: dict[str, float]) -> numpy.array: | |
| arr = [] | |
| for k, v in ratios.items(): | |
| arr.append(v) | |
| return numpy.array(arr) | |
| class FacialImage: | |
| def __init__(self): | |
| self.landmarks = [] | |
| self.width = 0 | |
| self.height = 0 | |
| def get_point_coordinates(self, point_num): | |
| point = self.landmarks[point_num] | |
| return point.x * self.width, point.y * self.height | |
| def get_distance_two_points(self, point_num_1, point_num_2): | |
| first = self.get_point_coordinates(point_num_1) | |
| second = self.get_point_coordinates(point_num_2) | |
| return dist(first, second) | |
| def get_ratio_between_two(self, ratio1_name, ratio2_name): | |
| first = self.get_distance_two_points(points[ratio1_name][0], points[ratio1_name][1]) | |
| second = self.get_distance_two_points(points[ratio2_name][0], points[ratio2_name][1]) | |
| return first / second | |
| def get_landmarks(self, image: numpy.ndarray): | |
| mp_face_mesh = mp.solutions.face_mesh | |
| face_mesh = mp_face_mesh.FaceMesh() | |
| # Image | |
| height, width, _ = image.shape | |
| rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
| # Facial landmarks | |
| result = face_mesh.process(rgb_image) | |
| for facial_landmarks in result.multi_face_landmarks: | |
| for i in range(0, 468): | |
| pt1 = facial_landmarks.landmark[i] | |
| x = int(pt1.x * width) | |
| y = int(pt1.y * height) | |
| cv2.circle(image, (x, y), 1, (255, 0, 0), -1) | |
| self.landmarks = result.multi_face_landmarks[0].landmark | |
| self.width = width | |
| self.height = height | |
| def calculate_ratios(self, image: numpy.ndarray, is_normalized=False): | |
| self.get_landmarks(image) | |
| ratios = { | |
| 'Under eyes/Interocular': self.get_ratio_between_two(Ratios.UNDER_EYES, Ratios.INTEROCULAR), | |
| 'Under eyes/Nose width': self.get_ratio_between_two(Ratios.UNDER_EYES, Ratios.NOSE_WIDTH), | |
| 'Mouth width/Interocular': self.get_ratio_between_two(Ratios.MOUTH_WIDTH, Ratios.INTEROCULAR), | |
| 'Upper lip-jaw/Interocular': self.get_ratio_between_two(Ratios.UPPER_LIP_TO_JAW, Ratios.INTEROCULAR), | |
| 'Upper lip-jaw/Nose width': self.get_ratio_between_two(Ratios.UPPER_LIP_TO_JAW, Ratios.NOSE_WIDTH), | |
| 'Interocular/Lip height': self.get_ratio_between_two(Ratios.INTEROCULAR, Ratios.LIPS_HEIGHT), | |
| 'Nose width/Interocular': self.get_ratio_between_two(Ratios.NOSE_WIDTH, Ratios.INTEROCULAR), | |
| 'Nose width/Upper lip height': self.get_ratio_between_two(Ratios.NOSE_WIDTH, Ratios.UPPER_LIP_HEIGHT), | |
| 'Interocular/Nose mouth height': self.get_ratio_between_two(Ratios.INTEROCULAR, | |
| Ratios.NOSE_TO_MOUTH_HEIGHT), | |
| 'Face top-eyebrows/Eyebrows-Nose': self.get_ratio_between_two(Ratios.FACE_TOP_TO_EYEBROWS, | |
| Ratios.EYEBROWS_TO_NOSE), | |
| 'Eyebrows-nose/Nose-jaw': self.get_ratio_between_two(Ratios.EYEBROWS_TO_NOSE, Ratios.NOSE_TO_JAW), | |
| 'Face top-eyebrows/Nose-Jaw': self.get_ratio_between_two(Ratios.FACE_TOP_TO_EYEBROWS, Ratios.NOSE_TO_JAW), | |
| 'Interocular/Nose width': self.get_ratio_between_two(Ratios.INTEROCULAR, Ratios.NOSE_WIDTH), | |
| 'Face height/Face width': self.get_ratio_between_two(Ratios.FACE_HEIGHT, Ratios.FACE_WIDTH), | |
| 'Lower eyebrow length': self.get_ratio_between_two(Ratios.LEFT_LOWER_EYEBROW_LENGTH, | |
| Ratios.RIGHT_LOWER_EYEBROW_LENGTH), | |
| 'Lower lip length': self.get_ratio_between_two(Ratios.LEFT_LOWER_LIP_LENGTH, Ratios.RIGHT_LOWER_LIP_LENGTH), | |
| 'Upper eyebrow': self.get_ratio_between_two(Ratios.LEFT_UPPER_EYEBROW_LENGTH, | |
| Ratios.RIGHT_UPPER_EYEBROW_LENGTH), | |
| 'Upper lip': self.get_ratio_between_two(Ratios.LEFT_UPPER_LIP_LENGTH, Ratios.RIGHT_UPPER_LIP_LENGTH), | |
| 'Nose': self.get_ratio_between_two(Ratios.LEFT_NOSE_WIDTH, Ratios.RIGHT_NOSE_WIDTH) | |
| } | |
| if is_normalized: | |
| return normalization(ratios), image | |
| return ratios, image | |