我家周围有三台IP摄像机,我想在检测到运动时拍摄一张图像。我想同时为所有3台摄像机运行运动捕捉算法
我设法为一个摄像头完成工作-打开流+运动检测算法+存储图像以防检测:
import cv2
cap3 = cv2.VideoCapture('http://X.X.X.X:XXXX/stream.mjpg')
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
while (True):
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 30, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap3.release()
cv2.destroyAllWindows()
我遇到的问题是,当我尝试为三个摄像头并行执行相同的工作时。 我所做的是在三个摄像头的while循环中复制相同的过程,当我这样做时,它开始运行几秒钟,然后我得到以下错误:
Traceback (most recent call last):
File "C:/Users/Guillaume/PycharmProjects/IPCAM/IPCAM2.py", line 54, in <module>
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
cv2.error: OpenCV(4.2.0) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
我在下面运行的代码:
import cv2
import numpy as np
from datetime import datetime
import time
cap2 = cv2.VideoCapture('rtsp://') # IPCAM2
cap = cv2.VideoCapture('rtsp://') # IPCAM1
cap3 = cv2.VideoCapture('http://') # RASP
def rescale_frame(frame, percent=75):
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
while (True):
ret1, frame11 = cap.read()
ret1, frame12 = cap.read()
ret2, frame21 = cap2.read()
ret2, frame22 = cap2.read()
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
diff1 = cv2.absdiff(frame11, frame12)
gray1 = cv2.cvtColor(diff1, cv2.COLOR_BGR2GRAY)
blur1 = cv2.GaussianBlur(gray1, (5, 5), 0)
_, tresh1 = cv2.threshold(blur1, 40, 255, cv2.THRESH_BINARY)
dilated1 = cv2.dilate(tresh1, None, iterations=3)
contours1, _ = cv2.findContours(dilated1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours1:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame11, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame11, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame11)
# cv2.line(frame, (0, 300), (200, 200), (0, 255, 0), 5)
resizedframe11 = rescale_frame(frame11, percent=75)
cv2.imshow('frame', resizedframe11)
frame11 = frame12
ret1, frame12 = cap.read()
diff2 = cv2.absdiff(frame21, frame22)
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
blur2 = cv2.GaussianBlur(gray2, (5, 5), 0)
_, tresh2 = cv2.threshold(blur2, 40, 255, cv2.THRESH_BINARY)
dilated2 = cv2.dilate(tresh2, None, iterations=3)
contours2, _ = cv2.findContours(dilated2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours2:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame21, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame21, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame21)
resizedframe21 = rescale_frame(frame21, percent=75)
cv2.imshow('frame2', resizedframe21)
frame21 = frame22
ret2, frame22 = cap2.read()
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 40, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
resizedframe31 = rescale_frame(frame31, percent=75)
cv2.imshow('frame3', resizedframe31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
谢谢卡提克和袋鼠的回答。 我设法用线程同时运行我的三个摄像头。我只是打开它们并显示一个调整大小的流。 还有一个问题,一个摄像头,然后一秒钟,在5到20秒之间的随机时间后停止。流停止,然后窗口关闭,没有任何消息。 在我看来,这似乎是由于从相机获取图像的滞后。。。使用openCV可以避免这种情况吗
再次感谢你的回答
下面是我使用的代码:
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