问题
I am trying to achieve results as shown on the video (Method 3 using netcat) https://www.youtube.com/watch?v=sYGdge3T30o
The point is to stream video from raspberry pi to ubuntu PC and process it using openCV and python.
I use command
raspivid -vf -n -w 640 -h 480 -o - -t 0 -b 2000000 | nc 192.168.0.20 5777
to stream the video to my PC and then on the PC I created name pipe 'fifo' and redirected the output
nc -l -p 5777 -v > fifo
then i am trying to read the pipe and display the result in the python script
import cv2
import sys
video_capture = cv2.VideoCapture(r'fifo')
video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, 640);
video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 480);
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
if ret == False:
pass
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
However I just end up with an error
[mp3 @ 0x18b2940] Header missing this error is produced by the command video_capture = cv2.VideoCapture(r'fifo')
When I redirect the output of netcat on PC to a file and then reads it in python the video works, however it is speed up by 10 times approximately.
I know the problem is with the python script, because the nc transmission works (to a file) but I am unable to find any clues.
How can I achieve the results as shown on the provided video (method 3) ?
回答1:
I too wanted to achieve the same result in that video. Initially I tried similar approach as yours, but it seems cv2.VideoCapture() fails to read from named pipes, some more pre-processing is required.
ffmpeg is the way to go ! You can install and compile ffmpeg by following the instructions given in this link: https://trac.ffmpeg.org/wiki/CompilationGuide/Ubuntu
Once it is installed, you can change your code like so:
import cv2
import subprocess as sp
import numpy
FFMPEG_BIN = "ffmpeg"
command = [ FFMPEG_BIN,
'-i', 'fifo', # fifo is the named pipe
'-pix_fmt', 'bgr24', # opencv requires bgr24 pixel format.
'-vcodec', 'rawvideo',
'-an','-sn', # we want to disable audio processing (there is no audio)
'-f', 'image2pipe', '-']
pipe = sp.Popen(command, stdout = sp.PIPE, bufsize=10**8)
while True:
# Capture frame-by-frame
raw_image = pipe.stdout.read(640*480*3)
# transform the byte read into a numpy array
image = numpy.fromstring(raw_image, dtype='uint8')
image = image.reshape((480,640,3)) # Notice how height is specified first and then width
if image is not None:
cv2.imshow('Video', image)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
pipe.stdout.flush()
cv2.destroyAllWindows()
No need to change any other thing on the raspberry pi side script.
This worked like a charm for me. The video lag was negligible. Hope it helps.
回答2:
I had a similar problem that I was working on, with a little more research I eventually stumbled upon the following:
Skip to the solution: https://stackoverflow.com/a/48675107/2355051
I ended up adapting this picamera python recipe
On the Raspberry Pi: (createStream.py)
import io
import socket
import struct
import time
import picamera
# Connect a client socket to my_server:8000 (change my_server to the
# hostname of your server)
client_socket = socket.socket()
client_socket.connect(('10.0.0.3', 777))
# Make a file-like object out of the connection
connection = client_socket.makefile('wb')
try:
with picamera.PiCamera() as camera:
camera.resolution = (1024, 768)
# Start a preview and let the camera warm up for 2 seconds
camera.start_preview()
time.sleep(2)
# Note the start time and construct a stream to hold image data
# temporarily (we could write it directly to connection but in this
# case we want to find out the size of each capture first to keep
# our protocol simple)
start = time.time()
stream = io.BytesIO()
for foo in camera.capture_continuous(stream, 'jpeg', use_video_port=True):
# Write the length of the capture to the stream and flush to
# ensure it actually gets sent
connection.write(struct.pack('<L', stream.tell()))
connection.flush()
# Rewind the stream and send the image data over the wire
stream.seek(0)
connection.write(stream.read())
# Reset the stream for the next capture
stream.seek(0)
stream.truncate()
# Write a length of zero to the stream to signal we're done
connection.write(struct.pack('<L', 0))
finally:
connection.close()
client_socket.close()
On the machine that is processing the stream: (processStream.py)
import io
import socket
import struct
import cv2
import numpy as np
# Start a socket listening for connections on 0.0.0.0:8000 (0.0.0.0 means
# all interfaces)
server_socket = socket.socket()
server_socket.bind(('0.0.0.0', 777))
server_socket.listen(0)
# Accept a single connection and make a file-like object out of it
connection = server_socket.accept()[0].makefile('rb')
try:
while True:
# Read the length of the image as a 32-bit unsigned int. If the
# length is zero, quit the loop
image_len = struct.unpack('<L', connection.read(struct.calcsize('<L')))[0]
if not image_len:
break
# Construct a stream to hold the image data and read the image
# data from the connection
image_stream = io.BytesIO()
image_stream.write(connection.read(image_len))
# Rewind the stream, open it as an image with opencv and do some
# processing on it
image_stream.seek(0)
image = Image.open(image_stream)
data = np.fromstring(image_stream.getvalue(), dtype=np.uint8)
imagedisp = cv2.imdecode(data, 1)
cv2.imshow("Frame",imagedisp)
cv2.waitKey(1) #imshow will not output an image if you do not use waitKey
cv2.destroyAllWindows() #cleanup windows
finally:
connection.close()
server_socket.close()
This solution has similar results to the video I referenced in my original question. Larger resolution frames increase latency of the feed, but this is tolerable for the purposes of my application.
First you need to run processStream.py, and then execute createStream.py on the Raspberry Pi
来源：https://stackoverflow.com/questions/35166111/opencv-python-reading-video-from-named-pipe