Question

我正在使用带PiCamera的Raspberry pi 3模型B对现场视频进行人员反击活动。以下是我们的代码：

# import the necessary packages
from __future__ import print_function
from imutils.object_detection import non_max_suppression
from imutils import paths
import numpy as np
import argparse
import imutils
import cv2
import RPi.GPIO as GPIO

from threading import Thread

from picamera.array import PiRGBArray
from picamera import PiCamera
import time

# initialize the camera and grab a reference to the raw camera capture
resX = 240
resY = 180
camera = PiCamera()
camera.resolution = (resX,resY)
camera.framerate = 10
rawCapture = PiRGBArray(camera, size=(resX, resY))

# initialize textIn and textOut values
textIn = 0
textOut = 0

print(time.strftime("%H_%M_%S"))
#fourcc = cv2.VideoWriter_fourcc(*'XVID')
fourcc = cv2.cv.CV_FOURCC(*'XVID')
out = cv2.VideoWriter(time.strftime("%H_%M_%S")+'.avi',fourcc, 20.0, (resX, resY))

# initialize the HOG descriptor/person detector
hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
detectFlag = 0
detectCounter = [0]
# allow the camera to warmup
time.sleep(0.1)

GPIO.setmode(GPIO.BOARD)

GPIO.setup(16, GPIO.OUT)

# methods for IN and OUT counters
def testIntersectionIn(x, y, z):

    if((x >= 75) and  (x <= 90) and (x < z[0]) and (z[0]>0)):
        print (x,z[0],"IN")
        return True
    return False

def testIntersectionOut(x, y, z):

    if((x >= 75) and  (x <= 90) and (x > z[0]) and (z[0]>0)):
        print (x,z[0],"OUT")
        return True

    return False

previousObj = (0,0)

def classfier(testImage,threadNum,capTime, detectCounter):
    global textIn, textOut, previousObj
    #print(threadNum,capTime)
    (rects, weights) = hog.detectMultiScale(testImage, winStride=(8, 8),
        padding=(16, 16), scale=1.1)

    rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])
    pick = non_max_suppression(rects, probs=None, overlapThresh=0.65)

    # draw the final bounding boxes

    cv2.line(image, (75,0), (75,192), (250, 0, 1), 2) #blue line
    cv2.line(image, (90,0), (90,192), (0, 0, 255), 2)#red line

    for (xA, yA, xB, yB) in pick:

        print("Image detected")
    print ("Previous Coord : ",previousObj)
        detectCounter[0] = 0
        cv2.rectangle(testImage, (xA, yA), (xB, yB), (0, 255, 0), 2)

    rectangleCenterPont = ((xA + xB) /2, (yA + yB) /2 )
    cv2.circle(testImage, rectangleCenterPont, 1, (0,0,255), 5)
    print (rectangleCenterPont)

    if(testIntersectionIn((xA + xB) /2, (yA + yB) /2,previousObj)):
            textIn += 1
                #print testIntersectionIn((x + x + w) / 2, (y + y + h) / 2)

        if(testIntersectionOut((xA + xB) /2, (yA + yB) /2,previousObj)):
            textOut += 1
                #print textOut

    previousObj = rectangleCenterPont


    cv2.putText(image, "In: {}".format(str(textIn)), (10, 50),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.putText(image, "Out: {}".format(str(textOut)), (10, 70),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    # print(pick,"\n");
    curTime = time.time()
    #print ("Total time from capture", curTime - capTime)
    out.write(testImage)
    cv2.imshow("After NMS", testImage)

# capture frames from the camera
i = 0
frameCount = 0
prevTime = time.time()
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    if (detectCounter[0] < 10):
        GPIO.output(16, GPIO.LOW)
        print ("Waiting ", detectCounter[0])
        detectCounter[0] += 1
    else:
        GPIO.output(16,GPIO.HIGH)
    image = frame.array
    captureTime = time.time()
    # print("FRAME Time", captureTime-prevTime)
    prevTime = captureTime

    # if frameCount == 0:
        # frameCount = 0
    #if i == 0:
    t1 = Thread(target = classfier, args = (image,i,captureTime,detectCounter))
    t1.start()
    threadPick = t1.join()


    # cv2.imshow("Frame", image)
    key = cv2.waitKey(1) & 0xFF

    # clear the stream in preparation for the next frame
    rawCapture.truncate(0)

     # if the `q` key was pressed, break from the loop
    if key == ord("q"):
        cleanup_stop_thread();
        sys.exit()
        t1.stop()

        break

在上面的代码中

我们在框架上画了两行
查找矩形的中心点
当这个中心点落在这两条线之间时，我们会增加计数器
IN和OUT计数器逻辑基于这两行的值

我遇到的问题是

人类上方的矩形不均匀。它消失并再次出现在帧中的随机点上。例如，当物体接近第一条线时，矩形消失，当它离开线时再次出现。所以这里矩形的中心点不会落在这些线之间，所以我们的计数器在这种情况下不会增加。在某些情况下，检测发生得很晚。一旦这个人进入框架，就不会这样。

请建议我以任何方式避免这种情况，并在任何人进入框架时始终保持该矩形。

人体检测不统一

0 个答案: