正在暂停GPIO.输出，而不影响其余代码

Question

我正在研究一个来自IP摄像机视频流的实时人脸识别程序，该程序在识别人脸时触发GPIO信号。在第一次识别人脸后，我需要GPIO在一定时间内不被激活(例如45秒)。

我试图在触发GPIO信号后插入time.sleep(45)，这似乎可以工作但是暂停45秒后，正在分析的视频流不再是实时的。它从人脸被识别的那一帧之后的那一帧开始，换句话说，有45秒的延迟。

我怎样才能暂停GPIO输出45秒，然后回到正在分析的实时视频流?

import cv2
import numpy as np
import os
import time
import RPi.GPIO as GPIO
relay = 23
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(relay, GPIO.OUT)
GPIO.output(relay, 1)
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath);
font = cv2.FONT_HERSHEY_SIMPLEX
#initiate id counter
id = 0
# names related to ids: example ==> Jenifer: id=1,  etc
names = ['None', 'Jenifer', 'Jenifer', 'Luciola'] 
# Initialize and start realtime video capture
cam = cv2.VideoCapture('ipcamera')
frame_rate = 1
prev = 0
# Define min window size to be recognized as a face
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)
while True:

time_elapsed = time.time() - prev
res, image = cam.read()
if time_elapsed > 1./frame_rate:
prev = time.time()
ret, img =cam.read()
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale( 
gray,
scaleFactor = 1.2,
minNeighbors = 5,
minSize = (int(minW), int(minH)),
)
for(x,y,w,h) in faces:
cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
id, confidence = recognizer.predict(gray[y:y+h,x:x+w])
# Check if confidence is less than 100 ==> "0" is perfect match 
if (confidence < 85):
id = names[id]
confidence = "  {0}%".format(round(100 - confidence))
GPIO.output(relay, 0)
print("Ouverture du portail")
time.sleep(1)
GPIO.output(relay, 1)
else:
GPIO.output(relay, 1)

cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)  

cv2.imshow('camera',img)
k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
# Do a bit of cleanup
print("n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()

负鼠的解决方案很有效。66行:

GPIO.output(relay, 1)
cam.release()
time.sleep(45)
cam = cv2.VideoCapture('ipcamera')

else:

Answer 1

您可以使用threading.Thread创建一个线程，该线程将在后台运行相机流，因此它将不受sleep函数的影响。你可以这样做:

from threading import Thread
import cv2
gray = None
minW = None
minH = None
def camera_stream():
def get_frames():
while True:
global minW
global minH
cv2.VideoCapture('ipcamera')
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)
res, image = cam.read()
gray_frame = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
yield gray_frame
while True:
global gray
gray = next(get_frames)

thread = Thread(target=camera_stream, daemon=True)
thread.start()
...

现在，无论您在哪里使用变量gray，它都应该使用在背景中不断运行的相机流中的下一帧。

Answer 2

您也可以尝试简单地定义一个函数来检查延迟是否已通过。

我修改了你的代码，还没有测试，但我认为它应该可以工作。

import numpy as np
import os
import time
import RPi.GPIO as GPIO
import cv2
relay = 23
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(relay, GPIO.OUT)
GPIO.output(relay, 1)
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath);
delay = 45
last_trigger = a = int(time.time()) - delay
def check_delay():
globals(last_trigger, delay)
current_time = int(time.time())
current_delay = current_time - last_trigger
if(current_delay < delay):
return False
else:
return True
font = cv2.FONT_HERSHEY_SIMPLEX
# initiate id counter
id = 0
# names related to ids: example ==> Jenifer: id=1,  etc
names = ['None', 'Jenifer', 'Jenifer', 'Luciola']
# Initialize and start realtime video capture
cam = cv2.VideoCapture('ipcamera')
frame_rate = 1
prev = 0
# Define min window size to be recognized as a face
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)
while True:
time_elapsed = time.time() - prev
res, image = cam.read()
if time_elapsed > 1. / frame_rate:
prev = time.time()
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(int(minW), int(minH)),
)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
id, confidence = recognizer.predict(gray[y:y + h, x:x + w])
# Check if confidence is less than 100 ==> "0" is perfect match
if (confidence < 85):
id = names[id]
confidence = "  {0}%".format(round(100 - confidence))
GPIO.output(relay, 0)
print("Ouverture du portail")
time.sleep(1)
if check_delay():
GPIO.output(relay, 1)
last_trigger = int(time.time())
else:
if check_delay():
GPIO.output(relay, 1)
last_trigger = int(time.time())
cv2.putText(img, str(id), (x + 5, y - 5), font, 1, (255, 255, 255), 2)
cv2.putText(img, str(confidence), (x + 5, y + h - 5), font, 1, (255, 255, 0), 1)
cv2.imshow('camera', img)
k = cv2.waitKey(10) & 0xff  # Press 'ESC' for exiting video
if k == 27:
break
# Do a bit of cleanup
print("n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()