119 lines
4.3 KiB
Python
119 lines
4.3 KiB
Python
import datetime
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import threading
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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 math
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from Post import post
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from PIL import ImageDraw, ImageFont
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from PIL import Image
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def fall_detect(cnts, defined_min_area, frame, prevX, prevY, xList, yList, centerV, alert, pre):
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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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try:
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ACS = 1 / (math.exp(ACS) + 1)
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except:
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ACS = 1 / (float('inf') + 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), 14)
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# cv2.putText(frame, "Fall Confidence: {0:.2f} ".format(P_FALL), (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
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# (0, 128, 255), 14)
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# cv2.putText(frame, "Angle: {0:.2f}".format(angle), (10, 220),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)
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# cv2.putText(frame, "AR: {0:.2f}".format(AR), (10, 237),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)
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# cv2.putText(frame, "Center Speed: {0:.2f}".format(centerV), (10, 256),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)
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# fall
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if P_FALL > 0.88:
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if alert > 3:
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# print("fall")
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font = ImageFont.truetype("simsun.ttc", 30, index=1)
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img_rd = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
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draw = ImageDraw.Draw(img_rd)
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draw.text((10, 10), text="Fall Detected", font=font,
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fill=(255, 0, 0))
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frame = cv2.cvtColor(np.array(img_rd), cv2.COLOR_RGB2BGR)
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time_snap = datetime.datetime.now()
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cv2.imwrite('fall_detection' + str(time_snap).replace(':', '') + '.jpg', frame)
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if (datetime.datetime.now() - pre).total_seconds() > 5:
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t = threading.Thread(
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target=post(event=3, imagePath='fall_detection' + str(time_snap).replace(':', '') + '.jpg'))
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t.setDaemon(False)
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t.start()
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pre = datetime.datetime.now()
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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 frame, alert, pre
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