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Receive NDI video stream in open cv

We have a videostream from camera with the help of NDI. How can we get it in OpenCV?
import cv2
cap = cv2.VideoCapture("tcp://192.168.1.69")
while cap.isOpened():
_, frame = cap.read()
# frame processing
We have tried the following variation of a string:
tcp://192.168.1.69
tcp://192.168.1.69:8080
http://192.168.1.69
http://192.168.1.69:8080
udp://192.168.1.69:8080
But we get an error every time. What is the correct string to use NDI stream?

A bit late and I'm sure you may have already come across the solution. You also failed to state the platform requirements. So the solution I have is currently Windows only at the moment.
The "NDI Virtual Input" driver allows an NDI network stream to be treated as a Webcam source. Thus you can just set the video capture source to the ID of the device. This requires the driver be installed on the client system
import cv2
cap = cv2.VideoCapture(1) # Could be any number, it's system specific, but it's u=usually 0, 1 etc.
while cap.isOpened():
_, frame = cap.read()
# frame processing

Have a look at PyNDI - I added some examples there to show you how to get NDI into openCV.
The SimpleSourceViewer is command line based, the GUIExample uses TKInter to give you an interface.

OpenCV & Python - Real time image (frame) processing

We're doing a project in school where we need to do basic image processing. Our goal is to use every video frame for the Raspberry Pi and do real time image processing.
We've tried to include raspistill in our python-program but so far nothing has worked. The goal of our project is to design a RC-car which follows a blue/red/whatever coloured line with help from image processing.
We thought it would be a good idea to make a python-program which does all image processing necessary, but we currently struggle with the idea of bringing recorded images into the python program. Is there a way to do this with picamera or should we try a different way?
For anyone curious, this is how our program currently looks
while True:
#camera = picamera.PiCamera()
#camera.capture('image1.jpg')
img = cv2.imread('image1.jpg')
width = img.shape[1]
height = img.shape[0]
height=height-1
for x in range (0,width):
if x>=0 and x<(width//2):
blue = img.item(height,x,0)
green = img.item(height,x,1)
red = img.item(height,x,2)
if red>green and red>blue:

OpenCV already contains functions to process live camera data.
This OpenCV documentation provides a simple example:
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
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',gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
Of course, you do not want to show the image but all your processing can be done there.
Remember to sleep a few hundred milliseconds so the pi does not overheat that much.
Edit:
"how exactly would I go about it though. I used "img = cv2.imread('image1.jpg')" all the time. What do I need to use instead to get the "img" variable right here? What do I use? And what is ret, for? :)"
ret indicates whether the read was successful. Exit program if not.
The read frame is nothing other than your img = cv2.imread('image1.jpg') so your detection code should work exactly the same.
The only difference is that your image does not need to be saved and reopened. Also for debugging purposes you can save the recorded image, like:
import cv2, time
cap = cv2.VideoCapture(0)
ret, frame = cap.read()
if ret:
cv2.imwrite(time.strftime("%Y%m%d-%H%M%S"), frame)
cap.release()

You can use picamera to acquire images.
To make it "real time", you can acquire data each X milliseconds. You need to set X depending on the power of your hardware (and the complexity of the openCV algorithm).
Here's an example (from http://picamera.readthedocs.io/en/release-1.10/api_camera.html#picamera.camera.PiCamera.capture_continuous) how to acquire 60 images per second using picamera:
import time
import picamera
with picamera.PiCamera() as camera:
camera.start_preview()
try:
for i, filename in enumerate(camera.capture_continuous('image{counter:02d}.jpg')):
print(filename)
time.sleep(1)
if i == 59:
break
finally:
camera.stop_preview()

camera does not work with opencv but does work with streamer

Im trying to use beaglebone with a usb camera using opencv and python.
Im having trouble capturing the image. However the commandline tool streamer seems to work.
For python I get:
>>> import cv2
>>> cap = cv2.VideoCapture(0)
>>> cap.read()
libv4l2: error dequeuing buf: No such device
VIDIOC_DQBUF: No such device
However from the command line I can do the following and it works fine:
streamer -f jpeg -o image.jpeg
There is a /dev/video0
And when I use lsusb I see the camera as
Bus 001 Device 003: ID 1908:2310 GEMBIRD
Any suggestions on how to get the camera to work with cv2

It turns out that this camera is very low rez and I had to specify that it was 320x240 as opposed to the default of 640x480. It just so happens that streamer was 320x240 by default anyway so it worked by default.
Here is the code.
import cv2
cap = cv2.VideoCapture(0)
cap.set(3,320)
cap.set(4,240)
status,image = cap.read()
cv2.imwrite("current.jpg", image)

Read Frames from RTSP Stream in Python

I have recently set up a Raspberry Pi camera and am streaming the frames over RTSP. While it may not be completely necessary, here is the command I am using the broadcast the video:
raspivid -o - -t 0 -w 1280 -h 800 |cvlc -vvv stream:///dev/stdin --sout '#rtp{sdp=rtsp://:8554/output.h264}' :demux=h264
This streams the video perfectly.
What I would now like to do is parse this stream with Python and read each frame individually. I would like to do some motion detection for surveillance purposes.
I am completely lost on where to start on this task. Can anyone point me to a good tutorial? If this is not achievable via Python, what tools/languages can I use to accomplish this?

Using the same method listed by "depu" worked perfectly for me.
I just replaced "video file" with "RTSP URL" of actual camera.
Example below worked on AXIS IP Camera.
(This was not working for a while in previous versions of OpenCV)
Works on OpenCV 3.4.1 Windows 10)
import cv2
cap = cv2.VideoCapture("rtsp://root:pass#192.168.0.91:554/axis-media/media.amp")
while(cap.isOpened()):
ret, frame = cap.read()
cv2.imshow('frame', frame)
if cv2.waitKey(20) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()

Bit of a hacky solution, but you can use the VLC python bindings (you can install it with pip install python-vlc) and play the stream:
import vlc
player=vlc.MediaPlayer('rtsp://:8554/output.h264')
player.play()
Then take a snapshot every second or so:
while 1:
time.sleep(1)
player.video_take_snapshot(0, '.snapshot.tmp.png', 0, 0)
And then you can use SimpleCV or something for processing (just load the image file '.snapshot.tmp.png' into your processing library).

use opencv
video=cv2.VideoCapture("rtsp url")
and then you can capture framse. read openCV documentation visit: https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_gui/py_video_display/py_video_display.html

Depending on the stream type, you can probably take a look at this project for some ideas.
https://code.google.com/p/python-mjpeg-over-rtsp-client/
If you want to be mega-pro, you could use something like http://opencv.org/ (Python modules available I believe) for handling the motion detection.

Here is yet one more option.
It's much more complicated than the other answers.
But this way, with just one connection to the camera, you could "fork" the same stream simultaneously to several multiprocesses, to the screen, recast it into multicast, write it to disk, etc.
Of course, just in the case you would need something like that (otherwise you'd prefer the earlier answers)
Let's create two independent python programs:
Server program (rtsp connection, decoding) server.py
Client program (reads frames from shared memory) client.py
Server must be started before the client, i.e.
python3 server.py
And then in another terminal:
python3 client.py
Here is the code:
(1) server.py
import time
from valkka.core import *
# YUV => RGB interpolation to the small size is done each 1000 milliseconds and passed on to the shmem ringbuffer
image_interval=1000
# define rgb image dimensions
width =1920//4
height =1080//4
# posix shared memory: identification tag and size of the ring buffer
shmem_name ="cam_example"
shmem_buffers =10
shmem_filter =RGBShmemFrameFilter(shmem_name, shmem_buffers, width, height)
sws_filter =SwScaleFrameFilter("sws_filter", width, height, shmem_filter)
interval_filter =TimeIntervalFrameFilter("interval_filter", image_interval, sws_filter)
avthread =AVThread("avthread",interval_filter)
av_in_filter =avthread.getFrameFilter()
livethread =LiveThread("livethread")
ctx =LiveConnectionContext(LiveConnectionType_rtsp, "rtsp://user:password#192.168.x.x", 1, av_in_filter)
avthread.startCall()
livethread.startCall()
avthread.decodingOnCall()
livethread.registerStreamCall(ctx)
livethread.playStreamCall(ctx)
# all those threads are written in cpp and they are running in the
# background. Sleep for 20 seconds - or do something else while
# the cpp threads are running and streaming video
time.sleep(20)
# stop threads
livethread.stopCall()
avthread.stopCall()
print("bye")
(2) client.py
import cv2
from valkka.api2 import ShmemRGBClient
width =1920//4
height =1080//4
# This identifies posix shared memory - must be same as in the server side
shmem_name ="cam_example"
# Size of the shmem ringbuffer - must be same as in the server side
shmem_buffers =10
client=ShmemRGBClient(
name =shmem_name,
n_ringbuffer =shmem_buffers,
width =width,
height =height,
mstimeout =1000, # client timeouts if nothing has been received in 1000 milliseconds
verbose =False
)
while True:
index, isize = client.pull()
if (index==None):
print("timeout")
else:
data =client.shmem_list[index][0:isize]
img =data.reshape((height,width,3))
img =cv2.GaussianBlur(img, (21, 21), 0)
cv2.imshow("valkka_opencv_demo",img)
cv2.waitKey(1)
If you got interested, check out some more in https://elsampsa.github.io/valkka-examples/

Hi reading frames from video can be achieved using python and OpenCV . Below is the sample code. Works fine with python and opencv2 version.
import cv2
import os
#Below code will capture the video frames and will sve it a folder (in current working directory)
dirname = 'myfolder'
#video path
cap = cv2.VideoCapture("your rtsp url")
count = 0
while(cap.isOpened()):
ret, frame = cap.read()
if not ret:
break
else:
cv2.imshow('frame', frame)
#The received "frame" will be saved. Or you can manipulate "frame" as per your needs.
name = "rec_frame"+str(count)+".jpg"
cv2.imwrite(os.path.join(dirname,name), frame)
count += 1
if cv2.waitKey(20) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()

Use in this
cv2.VideoCapture("rtsp://username:password#IPAddress:PortNO(rest of the link after the IPAdress)").

Problem with Opencv and Python

I'm new to python and Opencv and I tried to put in the following code to save an image to my computer from my webcam:
import cv
if __name__=='__main__':
pCapturedImage = cv.CaptureFromCAM(1)
rospy.sleep(0.5)
pSaveImg=cv.QueryFrame(pCapturedImage)
cv.SaveImage("test.jpg", pSaveImg)
But when I try to open it,
I find that the jpeg is empty.
Could someone please help?
Also, I tried a program to show what my webcam is seeing:
import cv
if __name__=='__main__':
cv.NamedWindow("camera",1)
capture=cv.CaptureFromCAM(0)
while True:
img=cv.QueryFrame(capture)
cv.ShowImage("camera", img)
if cv.WaitKey(10)==27:
break
cv.DestroyedWindow("camera")
But when I run it, I get an application that just shows me a gray screen.
Could someone help with this too?
Thanks.

Have you tried the demo programs? They show how to use the webcam among many other things.
For the first problem, I am not familiar with using cameras in opencv, but I got it to work by opening the capture (capture.open(device_id) in the code below)
Here is a working python sample (I use the newer c++ interface: imread, imwrite, VideoCapture, etc... which you can find in the OpenCV docs listed as "cv2" when it is available for python.):
import cv2
capture = cv2.VideoCapture() # this is the newer c++ interface
capture.open(0) # Use your device id; I think this is what you are missing.
image = capture.read()[1]
cv2.imwrite("test.jpg", image)
I got your second sample also working just by using open on the capture object:
import cv2
cv2.namedWindow("camera", 1) # this is where you will put the video images
capture = cv2.VideoCapture()
capture.open(0) # again, use your own device id
while True:
img = capture.read()[1]
cv2.imshow("camera", img)
if cv2.waitKey(10) == 27: # waiting for the esc key
break
cv2.destroyWindow("camera")