• Docs >
  • StreamReader Advanced Usages

StreamReader Advanced Usages

Author: Moto Hira

This tutorial is the continuation of StreamReader Basic Usages.

This shows how to use StreamReader for

  • Device inputs, such as microphone, webcam and screen recording

  • Generating synthetic audio / video

  • Applying preprocessing with custom filter expressions

import torch
import torchaudio

    from torchaudio.io import StreamReader
except ModuleNotFoundError:
        import google.colab

            To enable running this notebook in Google Colab, install the requisite
            third party libraries by running the following code:

            !add-apt-repository -y ppa:savoury1/ffmpeg4
            !apt-get -qq install -y ffmpeg
    except ModuleNotFoundError:

import IPython
import matplotlib.pyplot as plt

base_url = "https://download.pytorch.org/torchaudio/tutorial-assets"
AUDIO_URL = f"{base_url}/Lab41-SRI-VOiCES-src-sp0307-ch127535-sg0042.wav"
VIDEO_URL = f"{base_url}/stream-api/NASAs_Most_Scientifically_Complex_Space_Observatory_Requires_Precision-MP4.mp4"

Audio / Video device input

Given that the system has proper media devices and libavdevice is configured to use the devices, the streaming API can pull media streams from these devices.

To do this, we pass additional parameters format and option to the constructor. format specifies the device component and option dictionary is specific to the specified component.

The exact arguments to be passed depend on the system configuration. Please refer to https://ffmpeg.org/ffmpeg-devices.html for the detail.

The following example illustrates how one can do this on MacBook Pro.

First, we need to check the available devices.

$ ffmpeg -f avfoundation -list_devices true -i ""
[AVFoundation indev @ 0x143f04e50] AVFoundation video devices:
[AVFoundation indev @ 0x143f04e50] [0] FaceTime HD Camera
[AVFoundation indev @ 0x143f04e50] [1] Capture screen 0
[AVFoundation indev @ 0x143f04e50] AVFoundation audio devices:
[AVFoundation indev @ 0x143f04e50] [0] MacBook Pro Microphone

We use FaceTime HD Camera as video device (index 0) and MacBook Pro Microphone as audio device (index 0).

If we do not pass any option, the device uses its default configuration. The decoder might not support the configuration.

>>> StreamReader(
...     src="0:0",  # The first 0 means `FaceTime HD Camera`, and
...                 # the second 0 indicates `MacBook Pro Microphone`.
...     format="avfoundation",
... )
[avfoundation @ 0x125d4fe00] Selected framerate (29.970030) is not supported by the device.
[avfoundation @ 0x125d4fe00] Supported modes:
[avfoundation @ 0x125d4fe00]   1280x720@[1.000000 30.000000]fps
[avfoundation @ 0x125d4fe00]   640x480@[1.000000 30.000000]fps
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: Failed to open the input: 0:0

By providing option, we can change the format that the device streams to a format supported by decoder.

>>> streamer = StreamReader(
...     src="0:0",
...     format="avfoundation",
...     option={"framerate": "30", "pixel_format": "bgr0"},
... )
>>> for i in range(streamer.num_src_streams):
...     print(streamer.get_src_stream_info(i))
SourceVideoStream(media_type='video', codec='rawvideo', codec_long_name='raw video', format='bgr0', bit_rate=0, width=640, height=480, frame_rate=30.0)
SourceAudioStream(media_type='audio', codec='pcm_f32le', codec_long_name='PCM 32-bit floating point little-endian', format='flt', bit_rate=3072000, sample_rate=48000.0, num_channels=2)

Synthetic source streams

As a part of device integration, ffmpeg provides a “virtual device” interface. This interface provides synthetic audio / video data generation using libavfilter.

To use this, we set format=lavfi and provide a filter description to src.

The detail of filter description can be found at https://ffmpeg.org/ffmpeg-filters.html

Audio Examples

Sine wave


StreamReader(src="sine=sample_rate=8000:frequency=360", format="lavfi")

Signal with arbitral expression


# 5 Hz binaural beats on a 360 Hz carrier



StreamReader(src="anoisesrc=color=pink:sample_rate=8000:amplitude=0.5", format="lavfi")

Video Examples

Cellular automaton


StreamReader(src=f"cellauto", format="lavfi")



StreamReader(src=f"mandelbrot", format="lavfi")

MPlayer Test patterns


StreamReader(src=f"mptestsrc", format="lavfi")

John Conway’s life game


StreamReader(src=f"life", format="lavfi")

Sierpinski carpet/triangle fractal


StreamReader(src=f"sierpinski", format="lavfi")

Custom filters

When defining an output stream, you can use add_audio_stream() and add_video_stream() methods.

These methods take filter_desc argument, which is a string formatted according to ffmpeg’s filter expression.

The difference between add_basic_(audio|video)_stream and add_(audio|video)_stream is that add_basic_(audio|video)_stream constructs the filter expression and passes it to the same underlying implementation. Everything add_basic_(audio|video)_stream can be achieved with add_(audio|video)_stream.


  • When applying custom filters, the client code must convert the audio/video stream to one of the formats that torchaudio can convert to tensor format. This can be achieved, for example, by applying format=pix_fmts=rgb24 to video stream and aformat=sample_fmts=fltp to audio stream.

  • Each output stream has separate filter graph. Therefore, it is not possible to use different input/output streams for a filter expression. However, it is possible to split one input stream into multiple of them, and merge them later.

Audio Examples

# fmt: off
descs = [
    # No filtering
    # Apply a highpass filter then a lowpass filter
    # Manipulate spectrogram
    # Manipulate spectrogram
# fmt: on
sample_rate = 8000

streamer = StreamReader(AUDIO_URL)
for desc in descs:

chunks = next(streamer.stream())

def _display(i):
    print("filter_desc:", streamer.get_out_stream_info(i).filter_description)
    _, axs = plt.subplots(2, 1)
    waveform = chunks[i][:, 0]
    axs[0].set_ylim([-1, 1])
    plt.setp(axs[0].get_xticklabels(), visible=False)
    axs[1].specgram(waveform, Fs=sample_rate)
    return IPython.display.Audio(chunks[i].T, rate=sample_rate)


streamreader advanced tutorial
filter_desc: aresample=8000,anull,aformat=sample_fmts=fltp

Highpass / lowpass filter

streamreader advanced tutorial
filter_desc: aresample=8000,highpass=f=200,lowpass=f=1000,aformat=sample_fmts=fltp

FFT filter - Robot 🤖

streamreader advanced tutorial
filter_desc: aresample=8000,afftfilt=real='hypot(re,im)*sin(0)':imag='hypot(re,im)*cos(0)':win_size=512:overlap=0.75,aformat=sample_fmts=fltp

FFT filter - Whisper

streamreader advanced tutorial
filter_desc: aresample=8000,afftfilt=real='hypot(re,im)*cos((random(0)*2-1)*2*3.14)':imag='hypot(re,im)*sin((random(1)*2-1)*2*3.14)':win_size=128:overlap=0.8,aformat=sample_fmts=fltp

Video Examples

# fmt: off
descs = [
    # No effect
    # Split the input stream and apply horizontal flip to the right half.
        "split [main][tmp];"
        "[tmp] crop=iw/2:ih:0:0, hflip [flip];"
        "[main][flip] overlay=W/2:0"
    # Edge detection
    # Rotate image by randomly and fill the background with brown
    # Manipulate pixel values based on the coordinate
# fmt: on
streamer = StreamReader(VIDEO_URL)
for desc in descs:


chunks = next(streamer.stream())

def _display(i):
    print("filter_desc:", streamer.get_out_stream_info(i).filter_description)
    _, axs = plt.subplots(1, 3, figsize=(8, 1.9))
    chunk = chunks[i]
    for j in range(3):
        axs[j].imshow(chunk[10 * j + 1].permute(1, 2, 0))


streamreader advanced tutorial
filter_desc: fps=10,null,format=pix_fmts=rgb24


streamreader advanced tutorial
filter_desc: fps=10,split [main][tmp];[tmp] crop=iw/2:ih:0:0, hflip [flip];[main][flip] overlay=W/2:0,format=pix_fmts=rgb24

Edge detection

streamreader advanced tutorial
filter_desc: fps=10,edgedetect=mode=canny,format=pix_fmts=rgb24

Random rotation

streamreader advanced tutorial
filter_desc: fps=10,rotate=angle=-random(1)*PI:fillcolor=brown,format=pix_fmts=rgb24

Pixel manipulation

streamreader advanced tutorial
filter_desc: fps=10,geq=r='X/W*r(X,Y)':g='(1-X/W)*g(X,Y)':b='(H-Y)/H*b(X,Y)',format=pix_fmts=rgb24

Tag: torchaudio.io

Total running time of the script: ( 0 minutes 20.474 seconds)

Gallery generated by Sphinx-Gallery


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources