import cv2
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import imutils
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import dlib
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import numpy as np
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import random
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import time
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from imutils import face_utils
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class FaceDetector:
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def __init__(self, cap, win_width, win_height):
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self.cap = cap
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self.WIN_WIDTH = win_width
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self.WIN_HEIGHT = win_height
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self.detector = None # 人脸检测器
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self.predictor = None # 特征点检测器
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# 闪烁阈值
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self.EAR_THRESH = None
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self.MOUTH_THRESH = None
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# 总闪烁次数
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self.eye_flash_counter = None
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self.mouth_open_counter = None
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self.turn_left_counter = None
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self.turn_right_counter = None
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# 连续帧数阈值
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self.EAR_CONSTANT_FRAMES = None
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self.MOUTH_CONSTANT_FRAMES = None
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self.LEFT_CONSTANT_FRAMES = None
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self.RIGHT_CONSTANT_FRAMES = None
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# 连续帧计数器
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self.eye_flash_continuous_frame = 0
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self.mouth_open_continuous_frame = 0
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self.turn_left_continuous_frame = 0
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self.turn_right_continuous_frame = 0
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# 计算眼长宽比例 EAR值
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@staticmethod
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def count_EAR(eye):
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A = np.linalg.norm(eye[1] - eye[5])
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B = np.linalg.norm(eye[2] - eye[4])
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C = np.linalg.norm(eye[0] - eye[3])
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EAR = (A + B) / (2.0 * C)
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return EAR
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# 计算嘴长宽比例 MAR值
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@staticmethod
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def count_MAR(mouth):
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A = np.linalg.norm(mouth[1] - mouth[11])
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B = np.linalg.norm(mouth[2] - mouth[10])
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C = np.linalg.norm(mouth[3] - mouth[9])
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D = np.linalg.norm(mouth[4] - mouth[8])
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E = np.linalg.norm(mouth[5] - mouth[7])
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F = np.linalg.norm(mouth[0] - mouth[6]) # 水平欧几里德距离
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ratio = (A + B + C + D + E) / (5.0 * F)
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return ratio
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# 计算左右脸转动比例 FR值
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@staticmethod
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def count_FR(face):
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rightA = np.linalg.norm(face[0] - face[27])
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rightB = np.linalg.norm(face[2] - face[30])
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rightC = np.linalg.norm(face[4] - face[48])
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leftA = np.linalg.norm(face[16] - face[27])
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leftB = np.linalg.norm(face[14] - face[30])
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leftC = np.linalg.norm(face[12] - face[54])
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ratioA = rightA / leftA
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ratioB = rightB / leftB
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ratioC = rightC / leftC
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ratio = (ratioA + ratioB + ratioC) / 3
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return ratio
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# 本地活体检测
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def detect_face_local(self):
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self.detect_start_time = time.time()
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# 特征点检测器首次加载比较慢，通过判断减少后面加载的速度
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if self.detector is None:
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self.detector = dlib.get_frontal_face_detector()
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if self.predictor is None:
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self.predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')
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# 闪烁阈值
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self.EAR_THRESH = 0.25
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self.MOUTH_THRESH = 0.7
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# 总闪烁次数
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self.eye_flash_counter = 0
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self.mouth_open_counter = 0
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self.turn_left_counter = 0
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self.turn_right_counter = 0
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# 连续帧数阈值
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self.EAR_CONSTANT_FRAMES = 2
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self.MOUTH_CONSTANT_FRAMES = 2
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self.LEFT_CONSTANT_FRAMES = 4
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self.RIGHT_CONSTANT_FRAMES = 4
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# 连续帧计数器
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self.eye_flash_continuous_frame = 0
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self.mouth_open_continuous_frame = 0
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self.turn_left_continuous_frame = 0
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self.turn_right_continuous_frame = 0
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print("活体检测 初始化时间:", time.time() - self.detect_start_time)
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# 当前总帧数
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total_frame_counter = 0
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# 设置随机值
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now_flag = 0
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random_type = [0, 1, 2, 3]
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random.shuffle(random_type)
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random_eye_flash_number = random.randint(4, 6)
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random_mouth_open_number = random.randint(2, 4)
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print('请按照指示执行相关动作') # 简单输出提示信息
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# 抓取面部特征点的索引
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(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
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(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
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(mStart, mEnd) = face_utils.FACIAL_LANDMARKS_IDXS["mouth"]
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while self.cap.isOpened():
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ret, frame = self.cap.read()
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total_frame_counter += 1
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frame = imutils.resize(frame)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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rects = self.detector(gray, 0)
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if len(rects) == 1:
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shape = self.predictor(gray, rects[0])
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shape = face_utils.shape_to_np(shape)
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# 提取面部坐标
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left_eye = shape[lStart:lEnd]
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right_eye = shape[rStart:rEnd]
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mouth = shape[mStart:mEnd]
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# 计算长宽比
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left_EAR = self.count_EAR(left_eye)
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right_EAR = self.count_EAR(right_eye)
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mouth_MAR = self.count_MAR(mouth)
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leftRight_FR = self.count_FR(shape)
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average_EAR = (left_EAR + right_EAR) / 2.0
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# 计算左眼、右眼、嘴巴的凸包
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left_eye_hull = cv2.convexHull(left_eye)
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right_eye_hull = cv2.convexHull(right_eye)
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mouth_hull = cv2.convexHull(mouth)
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# 可视化
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cv2.drawContours(frame, [left_eye_hull], -1, (0, 255, 0), 1)
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cv2.drawContours(frame, [right_eye_hull], -1, (0, 255, 0), 1)
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cv2.drawContours(frame, [mouth_hull], -1, (0, 255, 0), 1)
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if now_flag >= 4:
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return True
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if random_type[now_flag] == 0:
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if self.turn_left_counter > 0:
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now_flag += 1
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else:
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self.check_left_turn(leftRight_FR)
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self.turn_right_counter = 0
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self.mouth_open_counter = 0
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self.eye_flash_counter = 0
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elif random_type[now_flag] == 1:
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if self.turn_right_counter > 0:
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now_flag += 1
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else:
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self.check_right_turn(leftRight_FR)
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self.turn_left_counter = 0
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self.mouth_open_counter = 0
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self.eye_flash_counter = 0
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elif random_type[now_flag] == 2:
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if self.mouth_open_counter >= random_mouth_open_number:
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now_flag += 1
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else:
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self.check_mouth_open(mouth_MAR)
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self.turn_right_counter = 0
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self.turn_left_counter = 0
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self.eye_flash_counter = 0
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elif random_type[now_flag] == 3:
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if self.eye_flash_counter >= random_eye_flash_number:
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now_flag += 1
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else:
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self.check_eye_flash(average_EAR)
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self.turn_right_counter = 0
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self.turn_left_counter = 0
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self.mouth_open_counter = 0
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elif len(rects) == 0:
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pass # 这里可以添加未检测到人脸的提示逻辑
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elif len(rects) > 1:
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pass # 这里可以添加检测到多张人脸的提示逻辑
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show_video = cv2.cvtColor(cv2.resize(frame, (self.WIN_WIDTH, self.WIN_HEIGHT)), cv2.COLOR_BGR2RGB)
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# 这里假设你有地方显示画面，实际需要关联到对应的界面元素
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if total_frame_counter >= 1000.0:
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return False
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def check_eye_flash(self, average_EAR):
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if average_EAR < self.EAR_THRESH:
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self.eye_flash_continuous_frame += 1
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else:
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if self.eye_flash_continuous_frame >= self.EAR_CONSTANT_FRAMES:
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self.eye_flash_counter += 1
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self.eye_flash_continuous_frame = 0
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def check_mouth_open(self, mouth_MAR):
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if mouth_MAR > self.MOUTH_THRESH:
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self.mouth_open_continuous_frame += 1
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else:
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if self.mouth_open_continuous_frame >= self.MOUTH_CONSTANT_FRAMES:
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self.mouth_open_counter += 1
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self.mouth_open_continuous_frame = 0
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def check_right_turn(self, leftRight_FR):
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if leftRight_FR <= 0.5:
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self.turn_right_continuous_frame += 1
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else:
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if self.turn_right_continuous_frame >= self.RIGHT_CONSTANT_FRAMES:
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self.turn_right_counter += 1
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self.turn_right_continuous_frame = 0
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def check_left_turn(self, leftRight_FR):
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if leftRight_FR >= 2.0:
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self.turn_left_continuous_frame += 1
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else:
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if self.turn_left_continuous_frame >= self.LEFT_CONSTANT_FRAMES:
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self.turn_left_counter += 1
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self.turn_left_continuous_frame = 0
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