def __init__(self, filename, *args,**kwargs):
super(MoviePlayer, self).__init__(*args,**kwargs)
TS_VIDEO_RGB24={ 'video1':(0, -1, {'pixel_format':PixelFormats.PIX_FMT_RGB24}), 'audio1':(1,-1,{})}
## create the reader object
self.mp = FFMpegReader(seek_before=0)
## open an audio-video file
self.mp.open(filename,TS_VIDEO_RGB24,buf_size=4096)
class MoviePlayer(Process):
def __init__(self, filename, *args,**kwargs):
super(MoviePlayer, self).__init__(*args,**kwargs)
TS_VIDEO_RGB24={ 'video1':(0, -1, {'pixel_format':PixelFormats.PIX_FMT_RGB24}), 'audio1':(1,-1,{})}
## create the reader object
self.mp = FFMpegReader(seek_before=0)
## open an audio-video file
self.mp.open(filename,TS_VIDEO_RGB24,buf_size=4096)
def get_size(self):
tracks = self.mp.get_tracks()
return tracks[0].get_size()
def set_buffer(self, buffer_data):
self.buffer_data = buffer_data
def render_to_buffer(self, frame):
buffer_array = np.frombuffer(self.buffer_data, 'B')
frame = np.flipud(frame)
frame = frame.reshape((1, -1))
buffer_array[:] = frame
def run(self):
tracks = self.mp.get_tracks()
tracks[0].set_observer(self.render_to_buffer)
rate = tracks[1].get_samplerate()
channels = tracks[1].get_channels()
fps = tracks[0].get_fps()
ap = AlsaSoundLazyPlayer(rate, channels, fps)
tracks[1].set_observer(ap.push_nowait)
self.mp.run()
def seek(self, pos=0):
if pos is not None and pos > 0:
self.mp.seek_to_seconds(pos)
def stop(self):
self.mp.close()
os.kill(self.pid, signal.SIGKILL)
0] * 0.02 #We only accept vertical lines where two edges of the laser line are close to each other
good_points = float(numpy.sum(numpy.where(mask1, 1, 0)))
if (good_points < 10):
return
good_indices = numpy.arange(maxes.shape[0])[mask1]
good_range = good_indices[-1] - good_indices[0]
fraction = good_points / float(good_range) #fraction of good points
goldenratio = 1.618
frameno += 1
if fraction > 0.7:
print fraction
extract_data(
numpy.arange(maxes.shape[0])[mask1], maxes[mask1, 1], camera)
scipy.misc.imsave("/tmp/saved-%03d.png" % frameno, r)
lab.figure(frameno, figsize=(5.0 * goldenratio, 5.0))
lab.plot(numpy.arange(0, maxes.shape[0])[mask1], maxes[mask1, 1], 'bo')
lab.plot(numpy.arange(0, maxes.shape[0]), 20 * (1 - mask1),
'g+') #mask out the ranges where maximums are bad
lab.ylabel("Position of maximum")
lab.savefig("/tmp/saved-%03d-plt2.png" % frameno)
mp = FFMpegReader()
print sys.argv[1]
mp.open(sys.argv[1])
tracks = mp.get_tracks()
video_track = tracks[0]
video_track.set_observer(observer)
#cProfile.run('mp.run()')
mp.run()
maxes = numpy.asarray([maxesgrad(r[:,i]) for i in xrange(r.shape[1])])
mask1 = (maxes[:,1]-maxes[:,0])<r.shape[0]*0.02 #We only accept vertical lines where two edges of the laser line are close to each other
good_points = float(numpy.sum(numpy.where(mask1,1,0)))
if(good_points<10):
return
good_indices=numpy.arange(maxes.shape[0])[mask1]
good_range = good_indices[-1]-good_indices[0]
fraction = good_points/float(good_range) #fraction of good points
goldenratio=1.618
frameno += 1
if fraction >0.7:
print fraction
extract_data(numpy.arange(maxes.shape[0])[mask1],maxes[mask1,1],camera)
scipy.misc.imsave("/tmp/saved-%03d.png" % frameno,r)
lab.figure(frameno,figsize=(5.0*goldenratio,5.0))
lab.plot(numpy.arange(0,maxes.shape[0])[mask1],maxes[mask1,1],'bo')
lab.plot(numpy.arange(0,maxes.shape[0]),20*(1-mask1),'g+') #mask out the ranges where maximums are bad
lab.ylabel("Position of maximum")
lab.savefig("/tmp/saved-%03d-plt2.png" % frameno)
mp = FFMpegReader()
print sys.argv[1]
mp.open(sys.argv[1])
tracks = mp.get_tracks()
video_track=tracks[0]
video_track.set_observer(observer)
#cProfile.run('mp.run()')
mp.run()
