103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
from imutils.video import VideoStream
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import imutils
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import time
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import cv2
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import numpy as np
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import statistics
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import queue
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import math
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def fall_detect(cnts, defined_min_area, frame, prevX, prevY, xList, yList, centerV, alert):
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for c in cnts:
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#exclusion
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if cv2.contourArea(c) < defined_min_area:
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continue
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# outer bounding box
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(x_b, y_b, w_b, h_b) = cv2.boundingRect(c)
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cv2.rectangle(frame, (x_b, y_b), (x_b + w_b, y_b + h_b), (0, 255, 255), 2) # 黄色矩形
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#rotating bounding box
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rect = cv2.minAreaRect(c) # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）
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box = cv2.boxPoints(rect) # 获取最小外接矩形的4个顶点坐标
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box = np.int0(box)
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cv2.drawContours(frame,[box],0,(0,0,255),2)
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#averaging line
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rows,cols = frame.shape[:2]
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[vx,vy,x,y] = cv2.fitLine(c, cv2.DIST_L2, 0, 0.01, 0.01)
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lefty = (-x * vy/vx) + y
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righty =((cols-x) * vy/vx)+y
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cv2.line(frame,(cols-1,righty),(0,lefty),(255,0,0),2)
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#ellipse
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elps = cv2.fitEllipse(c)
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(x, y), (MA, ma), angle = cv2.fitEllipse(c)
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cv2.ellipse(frame, elps,(255,0,0),3) #red
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#Aspect Ratio
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AR = MA/ma
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#Center Speed - acceleration
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prevX = 0.0
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prevY = 0.0
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centerSpeed =0
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if xList.full():
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prevX = statistics.median(list(xList.queue))
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prevY = statistics.median(list(yList.queue))
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xList.get()
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yList.get()
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xList.put(elps[0][0])
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yList.put(elps[0][1])
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X = statistics.median(list(xList.queue))
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Y = statistics.median(list(yList.queue))
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if xList.full():
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dx = abs(prevX-X)
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dy = abs(prevY-Y)
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centerV = math.sqrt(dx**2+dy**2)
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# calculate probabilities for the 4 features
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pAngle = (abs(angle-90)-50)/10
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pAngle = 1 / (math.exp(pAngle)+1)
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pAR = 10*AR - 5
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pAR = 1 / (math.exp(pAR) + 1)
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ACS = centerV - 9
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ACS = 1 / (math.exp(ACS) + 1)
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# print("pAngle : ", pAngle)
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# print("pAR : ", pAR)
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# print("ACS : ", ACS)
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#confidence
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P_FALL = pAngle * pAR * ACS + 0.5
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# print("P_FALL1 : ", P_FALL)
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P_FALL = 1/ (math.exp(-(P_FALL-0.65)*10)+1)
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# print("P_FALL2: ", P_FALL)
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#status display
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cv2.putText(frame, "Status : ", (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
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cv2.putText(frame, "Fall Confidence: {0:.2f} ".format(P_FALL), (10,50),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 128, 255), 2)
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# cv2.putText(frame, "Angle: {0:.2f}".format(angle), (10, 220),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 2)
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# cv2.putText(frame, "AR: {0:.2f}".format(AR), (10, 237),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 2)
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# cv2.putText(frame, "Center Speed: {0:.2f}".format(centerV), (10, 256),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 2)
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#fall
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if P_FALL > 0.88:
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if alert >= 8:
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print("fall")
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cv2.putText(frame, " Fall Detected", (82, 20),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
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# cv2.imwrite("report.jpg", frame)
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# send_alert.SendMail("report.jpg")
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alert = alert + 1
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else:
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alert = alert + 1
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return alert
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