使用Opencv和python连接NVR时如何从海康威视闭路电视网络摄像机获取图像进行图像处理?
How to get images from Hikvision CCTV IP camera for image processing when they are connected with NVR using Opencv and python?
我正在使用两台连接(DS-7600 系列)NVR 的 HIKVISION IP 摄像机 (DS-2CD204WFWD-I) 和 (DS-2CD214WFWD-I)。现在如何使用 Opencv 和 python 访问这些相机?
我已经尝试过这种方法,但它不起作用,代码是 运行,它没有得到框架。使用 NVR 软件摄像头正在显示实时流媒体和在 andoird 应用程序中,但我没有使用 python 获得任何帧。所以请帮助我如何使用 opencv 访问这些相机进行人脸识别。
import numpy as np
import cv2
cap = cv2.VideoCapture()
cap.open("rtsp://yourusername:yourpassword@172.16.30.248:555/
Streaming/channels/2/")
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Display the resulting frame
cv2.imshow('frame',ret)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
我希望两个摄像头都应该使用 opencv 打开。
嗯,通常的地址是:
主频道:rtsp://您的用户名:您的密码@172.16.30.248:555/
Streaming/Channels/101
第二个频道:rtsp://你的用户名:你的密码@172.16.30.248:555/
Streaming/Channels/102
当你想从摄像头获取流时,你不需要将 ipc 连接到 nvr。我非常了解海康威视相机,如果您对海康威视相机有任何疑问,可以给我发电子邮件(paulpeter@foxmail.com)。这是 python 基于 opencv 库的 Hikvsion 相机检测运动的代码
import cv2, time, pandas
from datetime import datetime
first_frame = None
status_list = [None,None]
times = []
df=pandas.DataFrame(columns=["Start","End"])
video = cv2.VideoCapture('rtsp://admin:Paxton10@10.199.27.128:554')
while True:
check, frame = video.read()
status = 0
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray,(21,21),0)
if first_frame is None:
first_frame=gray
continue
delta_frame=cv2.absdiff(first_frame,gray)
thresh_frame=cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
thresh_frame=cv2.dilate(thresh_frame, None, iterations=2)
(cnts,_)=cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in cnts:
if cv2.contourArea(contour) < 200000:
continue
status=1
(x, y, w, h)=cv2.boundingRect(contour)
cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 3)
status_list.append(status)
status_list=status_list[-2:]
if status_list[-1]==1 and status_list[-2]==0:
times.append(datetime.now())
if status_list[-1]==0 and status_list[-2]==1:
times.append(datetime.now())
#cv2.imshow("Gray Frame",gray)
#cv2.imshow("Delta Frame",delta_frame)
imS = cv2.resize(thresh_frame, (640, 480))
cv2.imshow("Threshold Frame",imS)
imS = cv2.resize(frame, (640, 480))
cv2.imshow("Color Frame",imS)
#cv2.imshow("Color Frame",frame)
key=cv2.waitKey(1)
if key == ord('q'):
if status == 1:
times.append(datetime.now())
break
print(status_list)
print(times)
for i in range(0, len(times), 2):
df = df.append({"Start": times[i],"End": times[i+1]}, ignore_index=True)
df.to_csv("Times.csv")
video.release()
cv2.destroyAllWindows
我正在使用两台连接(DS-7600 系列)NVR 的 HIKVISION IP 摄像机 (DS-2CD204WFWD-I) 和 (DS-2CD214WFWD-I)。现在如何使用 Opencv 和 python 访问这些相机?
我已经尝试过这种方法,但它不起作用,代码是 运行,它没有得到框架。使用 NVR 软件摄像头正在显示实时流媒体和在 andoird 应用程序中,但我没有使用 python 获得任何帧。所以请帮助我如何使用 opencv 访问这些相机进行人脸识别。
import numpy as np
import cv2
cap = cv2.VideoCapture()
cap.open("rtsp://yourusername:yourpassword@172.16.30.248:555/
Streaming/channels/2/")
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Display the resulting frame
cv2.imshow('frame',ret)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
我希望两个摄像头都应该使用 opencv 打开。
嗯,通常的地址是:
主频道:rtsp://您的用户名:您的密码@172.16.30.248:555/ Streaming/Channels/101
第二个频道:rtsp://你的用户名:你的密码@172.16.30.248:555/ Streaming/Channels/102
当你想从摄像头获取流时,你不需要将 ipc 连接到 nvr。我非常了解海康威视相机,如果您对海康威视相机有任何疑问,可以给我发电子邮件(paulpeter@foxmail.com)。这是 python 基于 opencv 库的 Hikvsion 相机检测运动的代码
import cv2, time, pandas
from datetime import datetime
first_frame = None
status_list = [None,None]
times = []
df=pandas.DataFrame(columns=["Start","End"])
video = cv2.VideoCapture('rtsp://admin:Paxton10@10.199.27.128:554')
while True:
check, frame = video.read()
status = 0
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray,(21,21),0)
if first_frame is None:
first_frame=gray
continue
delta_frame=cv2.absdiff(first_frame,gray)
thresh_frame=cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
thresh_frame=cv2.dilate(thresh_frame, None, iterations=2)
(cnts,_)=cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in cnts:
if cv2.contourArea(contour) < 200000:
continue
status=1
(x, y, w, h)=cv2.boundingRect(contour)
cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 3)
status_list.append(status)
status_list=status_list[-2:]
if status_list[-1]==1 and status_list[-2]==0:
times.append(datetime.now())
if status_list[-1]==0 and status_list[-2]==1:
times.append(datetime.now())
#cv2.imshow("Gray Frame",gray)
#cv2.imshow("Delta Frame",delta_frame)
imS = cv2.resize(thresh_frame, (640, 480))
cv2.imshow("Threshold Frame",imS)
imS = cv2.resize(frame, (640, 480))
cv2.imshow("Color Frame",imS)
#cv2.imshow("Color Frame",frame)
key=cv2.waitKey(1)
if key == ord('q'):
if status == 1:
times.append(datetime.now())
break
print(status_list)
print(times)
for i in range(0, len(times), 2):
df = df.append({"Start": times[i],"End": times[i+1]}, ignore_index=True)
df.to_csv("Times.csv")
video.release()
cv2.destroyAllWindows