I have gotten both OpenCV and PyAudio working however I am not sure how I would sync them together. I am unable to get a framerate from OpenCV and measuring the call time for a frame changes from moment to moment. However with PyAudio it's basis is grabbing a certain sample rate. How would I sync them to be at the same rate. I assume there is some standard or some way codecs do it. (I've tried google all I got was information on lip syncing :/).
OpenCV Frame rate
from __future__ import division
import time
import math
import cv2, cv
vc = cv2.VideoCapture(0)
# get the frame
while True:
before_read = time.time()
rval, frame = vc.read()
after_read = time.time()
if frame is not None:
print len(frame)
print math.ceil((1.0 / (after_read - before_read)))
cv2.imshow("preview", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
print "None..."
cv2.waitKey(1)
# display the frame
while True:
cv2.imshow("preview", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
Grabbing and saving audio
from sys import byteorder
from array import array
from struct import pack
import pyaudio
import wave
THRESHOLD = 500
CHUNK_SIZE = 1024
FORMAT = pyaudio.paInt16
RATE = 44100
def is_silent(snd_data):
"Returns 'True' if below the 'silent' threshold"
print "\n\n\n\n\n\n\n\n"
print max(snd_data)
print "\n\n\n\n\n\n\n\n"
return max(snd_data) < THRESHOLD
def normalize(snd_data):
"Average the volume out"
MAXIMUM = 16384
times = float(MAXIMUM)/max(abs(i) for i in snd_data)
r = array('h')
for i in snd_data:
r.append(int(i*times))
return r
def trim(snd_data):
"Trim the blank spots at the start and end"
def _trim(snd_data):
snd_started = False
r = array('h')
for i in snd_data:
if not snd_started and abs(i)>THRESHOLD:
snd_started = True
r.append(i)
elif snd_started:
r.append(i)
return r
# Trim to the left
snd_data = _trim(snd_data)
# Trim to the right
snd_data.reverse()
snd_data = _trim(snd_data)
snd_data.reverse()
return snd_data
def add_silence(snd_data, seconds):
"Add silence to the start and end of 'snd_data' of length 'seconds' (float)"
r = array('h', [0 for i in xrange(int(seconds*RATE))])
r.extend(snd_data)
r.extend([0 for i in xrange(int(seconds*RATE))])
return r
def record():
"""
Record a word or words from the microphone and
return the data as an array of signed shorts.
Normalizes the audio, trims silence from the
start and end, and pads with 0.5 seconds of
blank sound to make sure VLC et al can play
it without getting chopped off.
"""
p = pyaudio.PyAudio()
stream = p.open(format=FORMAT, channels=1, rate=RATE,
input=True, output=True,
frames_per_buffer=CHUNK_SIZE)
num_silent = 0
snd_started = False
r = array('h')
while 1:
# little endian, signed short
snd_data = array('h', stream.read(1024))
if byteorder == 'big':
snd_data.byteswap()
print "\n\n\n\n\n\n"
print len(snd_data)
print snd_data
r.extend(snd_data)
silent = is_silent(snd_data)
if silent and snd_started:
num_silent += 1
elif not silent and not snd_started:
snd_started = True
if snd_started and num_silent > 1:
break
sample_width = p.get_sample_size(FORMAT)
stream.stop_stream()
stream.close()
p.terminate()
r = normalize(r)
r = trim(r)
r = add_silence(r, 0.5)
return sample_width, r
def record_to_file(path):
"Records from the microphone and outputs the resulting data to 'path'"
sample_width, data = record()
data = pack('<' + ('h'*len(data)), *data)
wf = wave.open(path, 'wb')
wf.setnchannels(1)
wf.setsampwidth(sample_width)
wf.setframerate(RATE)
wf.writeframes(data)
wf.close()
if __name__ == '__main__':
print("please speak a word into the microphone")
record_to_file('demo.wav')
print("done - result written to demo.wav")
I think you'd be better off using either GSreamer or ffmpeg, or if you're on Windows, DirectShow. These libs can handle both audio and video, and should have some kind of a Multiplexer to allow you to mix video and audio properly.
But if you really want to do this using Opencv, you should be able to use VideoCapture
to get the frame rate, have you tried using this?
fps = cv.GetCaptureProperty(vc, CV_CAP_PROP_FPS)
Another way would be to estimate fps as number of frames divided by duration:
nFrames = cv.GetCaptureProperty(vc, CV_CAP_PROP_FRAME_COUNT)
cv.SetCaptureProperty(vc, CV_CAP_PROP_POS_AVI_RATIO, 1)
duration = cv.GetCaptureProperty(vc, CV_CAP_PROP_POS_MSEC)
fps = 1000 * nFrames / duration;
I'm not sure I understand what you were trying to do here:
before_read = time.time()
rval, frame = vc.read()
after_read = time.time()
It seems to me that doing after_read - before_read
only measures how long it took for OpenCV to load the next frame, it doesn't measure the fps. OpenCV is not trying to do playback, it's only loading frames and it'll try to do so the fastest it can and I think there's no way to configure that. I think that putting a waitKey(1/fps)
after displaying each frame will achieve what you're looking for.
You could have 2 counters 1 for audio and one for video. The video counter will become +(1/fps) when showing an image and audio +sec where sec the seconds of audio you are writing to the stream each time. Then on audio part of the code you can do something like While audiosec-videosec>=0.05: # Audio is ahead time.sleep(0.05)
And on video part While videosec-audiosec>=0.2:# video is ahead time.sleep(0.2)
You can play with the numbers
This is how i achieve some sort of synchronization on my own video player project using pyaudio recently ffmpeg instead of cv2.
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