python+dlib活体检测

'''活体检测''' # import the necessary packages from scipy.spatial import distance as dist from imutils.video import FileVideoStream from imutils.video import VideoStream from imutils import face_utils import numpy as np import argparse import imutils import time import dlib import cv2 import random def eye_aspect_ratio(eye): # compute the euclidean distances between the two sets of vertical eye landmarks (x, y)-coordinates # 计算两组垂直眼睛地标（x，y）坐标之间的欧氏距离 A = dist.euclidean(eye[1], eye[5]) # (43, 47) 垂直欧几里德距离 B = dist.euclidean(eye[2], eye[4]) # (44, 46) # compute the euclidean distance between the horizontal eye landmark (x, y)-coordinates # 计算水平眼睛地标（x，y）坐标之间的欧氏距离 C = dist.euclidean(eye[0], eye[3]) # (42, 45) 水平欧几里德距离 # compute the eye aspect ratio 长宽比 ear = (A + B) / (2.0 * C) # return the eye aspect ratio return ear def mouth_aspect_ratio(mouth): A = dist.euclidean(mouth[1], mouth[11]) B = dist.euclidean(mouth[2], mouth[10]) C = dist.euclidean(mouth[3], mouth[9]) D = dist.euclidean(mouth[4], mouth[8]) E = dist.euclidean(mouth[5], mouth[7]) F = dist.euclidean(mouth[0], mouth[6]) # 水平欧几里德距离 ratio = (A + B + C + D + E) / (5.0 * F) return ratio def left_right_face_ratio(face): rightA = dist.euclidean(face[0], face[27]) rightB = dist.euclidean(face[2], face[30]) rightC = dist.euclidean(face[4], face[48]) leftA = dist.euclidean(face[16], face[27]) leftB = dist.euclidean(face[14], face[30]) leftC = dist.euclidean(face[12], face[54]) ratioA = rightA / leftA ratioB = rightB / leftB ratioC = rightC / leftC ratio = (ratioA + ratioB + ratioC) / 3 return ratio # 左转大于2.0，右转小于0.5 # define two constants, one for the eye aspect ratio to indicate # blink and then a second constant for the number of consecutive # frames the eye must be below the threshold EYE_AR_THRESH = 0.25 EYE_AR_CONSEC_FRAMES = 2 # initialize the frame counters and the total number of blinks COUNTER = 0 TOTAL = 0 OPEN_MOUTH_COUNTER = 0 MOUTH_TOTAL = 0 TRUN_LEFT_TOTAL = 0 TRUN_RIGHT_TOTAL = 0 TRUN_LEFT_COUNTER = 0 TRUN_RIGHT_COUNTER = 0 random_number = random.randint(1, 2) # initialize dlib's face detector (HOG-based) and then create # the facial landmark predictor print("[INFO] loading facial landmark predictor...") detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(r'D:\Python\OpenCV\shape_predictor_68_face_landmarks.dat') # 这里需要修改成你自己的路径 # grab the indexes of the facial landmarks for the left and # right eye, respectively (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"] # (42, 48) (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"] # (36, 42) (mStart, mEnd) = face_utils.FACIAL_LANDMARKS_IDXS["mouth"] # (48, 68) # start the video stream thread print("[INFO] starting video stream thread...") #vs = FileVideoStream(args["video"]).start() fileStream = True # vs = VideoStream(src=0).start() video_capture = cv2.VideoCapture(0) fileStream = False textColor = (255, 0, 0) # loop over frames from the video stream while True: ret,frame = video_capture.read() frame = imutils.resize(frame) # , width=450) gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # detect faces in the grayscale frame rects = detector(gray, 0) # loop over the face detections for rect in rects: shape = predictor(gray, rect) shape = face_utils.shape_to_np(shape) # extract the left and right eye coordinates, then use the # coordinates to compute the eye aspect ratio for both eyes leftEye = shape[lStart:lEnd] rightEye = shape[rStart:rEnd] mouth = shape[mStart:mEnd] leftEAR = eye_aspect_ratio(leftEye) rightEAR = eye_aspect_ratio(rightEye) mouthRatio = mouth_aspect_ratio(mouth) leftRightRatio = left_right_face_ratio(shape) # average the eye aspect ratio together for both eyes ear = (leftEAR + rightEAR) / 2.0 # 欧几里德距离，垂直/水平比 # compute the convex hull for the left and right eye, then # visualize each of the eyes leftEyeHull = cv2.convexHull(leftEye) rightEyeHull = cv2.convexHull(rightEye) mouthHull = cv2.convexHull(mouth) cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1) cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1) cv2.drawContours(frame, [mouthHull], -1, (0, 255, 0), 1) print("leftRightRatio:",leftRightRatio) # # print("mouthRatio:",mouthRatio) # 0.387004875451 1.01599394304 if mouthRatio > 0.7: OPEN_MOUTH_COUNTER += 1 else: if OPEN_MOUTH_COUNTER >= 2: MOUTH_TOTAL += 1 OPEN_MOUTH_COUNTER = 0 if leftRightRatio >= 2.0: TRUN_LEFT_COUNTER += 1 elif leftRightRatio <= 0.5: TRUN_RIGHT_COUNTER += 1 else: if TRUN_LEFT_COUNTER >= 2: TRUN_LEFT_TOTAL += 1 if TRUN_RIGHT_COUNTER >= 2: TRUN_RIGHT_TOTAL += 1 TRUN_LEFT_COUNTER = 0 TRUN_RIGHT_COUNTER = 0 # check to see if the eye aspect ratio is below the blink # threshold, and if so, increment the blink frame counter if ear < EYE_AR_THRESH: COUNTER += 1 # otherwise, the eye aspect ratio is not below the blink # threshold else: # if the eyes were closed for a sufficient number of # then increment the total number of blinks 闭眼时间大于等于2帧图片 if COUNTER >= EYE_AR_CONSEC_FRAMES: TOTAL += 1 # 检测完成后，眨眼重新检测 if TRUN_RIGHT_TOTAL >= 1 and TRUN_LEFT_TOTAL >= 1 and MOUTH_TOTAL >= 1: TRUN_LEFT_TOTAL = 0 TRUN_RIGHT_TOTAL = 0 MOUTH_TOTAL = 0 random_number = random.randint(1, 2) # reset the eye frame counter COUNTER = 0 if random_number == 1: if TRUN_LEFT_TOTAL > 0: if TRUN_RIGHT_TOTAL > 0: if MOUTH_TOTAL > 0: cv2.putText(frame, "live detection finish", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) else: cv2.putText(frame, "Open Mouth", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) else: cv2.putText(frame, "Trun Right Face", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) MOUTH_TOTAL = 0 else: cv2.putText(frame, "Trun Left Face", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) MOUTH_TOTAL = 0 TRUN_RIGHT_TOTAL = 0 elif random_number == 2: if MOUTH_TOTAL > 0: if TRUN_RIGHT_TOTAL > 0: if TRUN_LEFT_TOTAL > 0: cv2.putText(frame, "live detection finish", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) else: cv2.putText(frame, "Trun Left Face", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) else: cv2.putText(frame, "Trun Right Face", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) TRUN_LEFT_TOTAL = 0 else: cv2.putText(frame, "Open Mouth", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, textColor, 2) TRUN_LEFT_TOTAL = 0 TRUN_RIGHT_TOTAL = 0 if len(rects) == 0: cv2.putText(frame, "No Face Detected!", (200, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0 ,255), 2) # show the frame cv2.imshow("Frame", frame) if cv2.waitKey(30) & 0xFF == ord('q'): break video_capture.release() cv2.destroyAllWindows()