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Sur d’autres sites (8132)
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How can I mux H.264 RTP output into a container using FFMPEG ?
23 septembre 2013, par GradI am working on the effects of network losses in video transmission. In order to simulate the network losses I use a simple program which drops random RTP packets from the output of H.264 RTP encoding.
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| RTP Header #1 | RTP Payload #1 | RTP Header #2 | RTP Payload #2 |...
----------------------------------------------------------------------I want to make a subjective test with these bitstreams and it's very inconvenient to crowdsource this subjective test with GBs of video data. So, I want to mux these bitstreams into a container (i.e. AVI) by using FFMPEG. I have tried to decode these bitstreams with FFMPEG and FFPLAY ; however, both of them didn't work. I also tried the following command and it didn't work, either.
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How can fix CalledProcessError : in ffmpeg
7 décembre 2020, par MarioI hope someone can help to troubleshoot this problem. I'm trying to save the loss plots out of Keras in the form of the following animation.






but I have been facing the following error, and ultimately I can't save the animation :



MovieWriter stderr:
[h264_v4l2m2m @ 0x55a67176f430] Could not find a valid device
[h264_v4l2m2m @ 0x55a67176f430] can't configure encoder
Error initializing output stream 0:0 -- Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height

---------------------------------------------------------------------------
BrokenPipeError Traceback (most recent call last)
~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in saving(self, fig, outfile, dpi, *args, **kwargs)
 229 try:
--> 230 yield self
 231 finally:

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in save(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)
 1155 frame_number += 1
-> 1156 writer.grab_frame(**savefig_kwargs)
 1157 

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in grab_frame(self, **savefig_kwargs)
 383 self.fig.savefig(self._frame_sink(), format=self.frame_format,
--> 384 dpi=self.dpi, **savefig_kwargs)
 385 

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/figure.py in savefig(self, fname, transparent, **kwargs)
 2179 
-> 2180 self.canvas.print_figure(fname, **kwargs)
 2181 

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)
 2081 bbox_inches_restore=_bbox_inches_restore,
-> 2082 **kwargs)
 2083 finally:

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py in print_raw(self, filename_or_obj, *args, **kwargs)
 445 cbook.open_file_cm(filename_or_obj, "wb") as fh:
--> 446 fh.write(renderer._renderer.buffer_rgba())
 447 

BrokenPipeError: [Errno 32] Broken pipe

During handling of the above exception, another exception occurred:

CalledProcessError Traceback (most recent call last)
 in <module>
 17 print(f'{model_type.upper()} Train Time: {Timer} sec')
 18 
---> 19 create_loss_animation(model_type, hist.history['loss'], hist.history['val_loss'], epoch)
 20 
 21 evaluate(model, trainX, trainY, testX, testY, scores_train, scores_test)

 in create_loss_animation(model_type, loss_hist, val_loss_hist, epoch)
 34 
 35 ani = matplotlib.animation.FuncAnimation(fig, animate, fargs=(l1, l2, loss, val_loss, title), repeat=True, interval=1000, repeat_delay=1000)
---> 36 ani.save(f'loss_animation_{model_type}_oneDataset.mp4', writer=writer)

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in save(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)
 1154 progress_callback(frame_number, total_frames)
 1155 frame_number += 1
-> 1156 writer.grab_frame(**savefig_kwargs)
 1157 
 1158 # Reconnect signal for first draw if necessary

~/anaconda3/envs/CR7/lib/python3.6/contextlib.py in __exit__(self, type, value, traceback)
 97 value = type()
 98 try:
---> 99 self.gen.throw(type, value, traceback)
 100 except StopIteration as exc:
 101 # Suppress StopIteration *unless* it's the same exception that

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in saving(self, fig, outfile, dpi, *args, **kwargs)
 230 yield self
 231 finally:
--> 232 self.finish()
 233 
 234 

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in finish(self)
 365 def finish(self):
 366 '''Finish any processing for writing the movie.'''
--> 367 self.cleanup()
 368 
 369 def grab_frame(self, **savefig_kwargs):

~/anaconda3/envs/CR7/lib/python3.6/site-packages/matplotlib/animation.py in cleanup(self)
 409 if self._proc.returncode:
 410 raise subprocess.CalledProcessError(
--> 411 self._proc.returncode, self._proc.args, out, err)
 412 
 413 @classmethod

CalledProcessError: Command '['/usr/bin/ffmpeg', '-f', 'rawvideo', '-vcodec', 'rawvideo', '-s', '720x720', '-pix_fmt', 
'rgba', '-r', '5', '-loglevel', 'error', '-i', 'pipe:', '-vcodec', 'h264', '-pix_fmt', 'yuv420p', '-b', '800k', '-y', 
'loss_animation_CNN_oneDataset.mp4']' returned non-zero exit status 1.
</module>


I tried to ignore the error by this answer but it seems it's not the case. I also checked similar case but its answer for getting a static git binary is not my cas as well since not especial converting PNG to MP4 !



My code is as follows :



plt.rcParams['animation.ffmpeg_path'] = '/usr/bin/ffmpeg'

def animate(i, data1, data2, line1, line2):
 temp1 = data1.iloc[:int(i+1)]
 temp2 = data2.iloc[:int(i+1)]

 line1.set_data(temp1.index, temp1.value)
 line2.set_data(temp2.index, temp2.value)

 return (line1, line2)


def create_loss_animation(model_type, data1, data2):
 fig = plt.figure()
 plt.title(f'Loss on Train & Test', fontsize=25)
 plt.xlabel('Epoch', fontsize=20)
 plt.ylabel('Loss MSE for Sx-Sy & Sxy', fontsize=20)
 plt.xlim(min(data1.index.min(), data2.index.min()), max(data1.index.max(), data2.index.max()))
 plt.ylim(min(data1.value.min(), data2.value.min()), max(data1.value.max(), data2.value.max()))

 l1, = plt.plot([], [], 'o-', label='Train Loss', color='b', markevery=[-1])
 l2, = plt.plot([], [], 'o-', label='Test Loss', color='r', markevery=[-1])
 plt.legend(loc='center right', fontsize='xx-large')

 Writer = animation.writers['ffmpeg']
 writer = Writer(fps=5, bitrate=1800)

 ani = matplotlib.animation.FuncAnimation(fig, animate, fargs=(data1, data2, l1, l2), repeat=True, interval=1000, repeat_delay=1000)
 ani.save(f'{model_type}.mp4', writer=writer)

# create datasets
x = np.linspace(0,150,50)
y1 = 41*np.exp(-x/20)
y2 = 35*np.exp(-x/50)

my_data_number_1 = pd.DataFrame({'x':x, 'value':y1}).set_index('x')
my_data_number_2 = pd.DataFrame({'x':x, 'value':y2}).set_index('x')

create_loss_animation('test', my_data_number_1, my_data_number_2)


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