疲勞檢測

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pan.baidu.com/s/1Ng_-utB8BSrXlgVelc8ovw

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#導(dǎo)入工具包 from scipy.spatial import distance as dist from collections import OrderedDict import numpy as np import argparse import time import dlib import cv2FACIAL_LANDMARKS_68_IDXS = OrderedDict([("mouth", (48, 68)),("right_eyebrow", (17, 22)),("left_eyebrow", (22, 27)),("right_eye", (36, 42)),("left_eye", (42, 48)),("nose", (27, 36)),("jaw", (0, 17)) ])# http://vision.fe.uni-lj.si/cvww2016/proceedings/papers/05.pdf def eye_aspect_ratio(eye):# 計算距離，豎直的A = dist.euclidean(eye[1], eye[5])B = dist.euclidean(eye[2], eye[4])# 計算距離，水平的C = dist.euclidean(eye[0], eye[3])# ear值ear = (A + B) / (2.0 * C)return ear# 輸入?yún)?shù) ap = argparse.ArgumentParser() ap.add_argument("-p", "--shape-predictor", required=True,help="path to facial landmark predictor") ap.add_argument("-v", "--video", type=str, default="",help="path to input video file") args = vars(ap.parse_args())# 設(shè)置判斷參數(shù) EYE_AR_THRESH = 0.3 EYE_AR_CONSEC_FRAMES = 3# 初始化計數(shù)器 COUNTER = 0 TOTAL = 0# 檢測與定位工具 print("[INFO] loading facial landmark predictor...") detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(args["shape_predictor"])# 分別取兩個眼睛區(qū)域 (lStart, lEnd) = FACIAL_LANDMARKS_68_IDXS["left_eye"] (rStart, rEnd) = FACIAL_LANDMARKS_68_IDXS["right_eye"]# 讀取視頻 print("[INFO] starting video stream thread...") vs = cv2.VideoCapture(args["video"]) #vs = FileVideoStream(args["video"]).start() time.sleep(1.0)def shape_to_np(shape, dtype="int"):# 創(chuàng)建68*2coords = np.zeros((shape.num_parts, 2), dtype=dtype)# 遍歷每一個關(guān)鍵點# 得到坐標(biāo)for i in range(0, shape.num_parts):coords[i] = (shape.part(i).x, shape.part(i).y)return coords# 遍歷每一幀 while True:# 預(yù)處理frame = vs.read()[1]if frame is None:break(h, w) = frame.shape[:2]width=1200r = width / float(w)dim = (width, int(h * r))frame = cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)# 檢測人臉rects = detector(gray, 0)# 遍歷每一個檢測到的人臉for rect in rects:# 獲取坐標(biāo)shape = predictor(gray, rect)shape = shape_to_np(shape)# 分別計算ear值leftEye = shape[lStart:lEnd]rightEye = shape[rStart:rEnd]leftEAR = eye_aspect_ratio(leftEye)rightEAR = eye_aspect_ratio(rightEye)# 算一個平均的ear = (leftEAR + rightEAR) / 2.0# 繪制眼睛區(qū)域leftEyeHull = cv2.convexHull(leftEye)rightEyeHull = cv2.convexHull(rightEye)cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)# 檢查是否滿足閾值if ear < EYE_AR_THRESH:COUNTER += 1else:# 如果連續(xù)幾幀都是閉眼的，總數(shù)算一次if COUNTER >= EYE_AR_CONSEC_FRAMES:TOTAL += 1# 重置COUNTER = 0# 顯示cv2.putText(frame, "Blinks: {}".format(TOTAL), (10, 30),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)cv2.imshow("Frame", frame)key = cv2.waitKey(10) & 0xFFif key == 27:breakvs.release() cv2.destroyAllWindows()

　　

OpenCV計算機視覺實戰(zhàn)?

唐宇迪老師的課程講的挺好的 就是貴了點

課程目錄

01課程簡介與環(huán)境配置

02圖像基本操作

03閾值與平滑處理

04圖像形態(tài)學(xué)操作

05圖像梯度計算

06邊緣檢測

07圖像金字塔與輪廓檢測

08直方圖與傅里葉變換

09項目實戰(zhàn)-信用卡數(shù)字識別

10項目實戰(zhàn)-文檔掃描OCR識別

11圖像特征-harris

12圖像特征-sift

13案例實戰(zhàn)-全景圖像拼接

14項目實戰(zhàn)-停車場車位識別

15項目實戰(zhàn)-答題卡識別判卷

16背景建模

17光流估計

18Opencv的DNN模塊

19項目實戰(zhàn)-目標(biāo)追蹤

20卷積原理與操作

21項目實戰(zhàn)-疲勞檢測

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pan。baidu。com/s/1Ng_-utB8BSrXlgVelc8ovw

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轉(zhuǎn)載于:https://www.cnblogs.com/zhaofuyun/p/11356955.html

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