streaming_api_tutorial.py 28.1 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
"""
Media Stream API
================

This tutorial shows how to use torchaudio's I/O stream API to
fetch and decode audio/video data and apply preprocessings that
libavfilter provides.

"""

######################################################################
# 1. Overview
# -----------
#
# Streaming API leverages the powerful I/O features of ffmpeg.
#
# It can
#  - Load audio/video in variety of formats
#  - Load audio/video from local/remote source
#  - Load audio/video from microphone, camera and screen
#  - Generate synthetic audio/video signals.
#  - Load audio/video chunk by chunk
#  - Change the sample rate / frame rate, image size, on-the-fly
#  - Apply filters and preprocessings
#
# The streaming API works in three steps.
#
# 1. Open media source (file, device, synthetic pattern generator)
# 2. Configure output stream
# 3. Stream the media
#
# At this moment, the features that the ffmpeg integration provides
# are limited to the form of
#
# `<some media source> -> <optional processing> -> <tensor>`
#
# If you have other forms that can be useful to your usecases,
# (such as integration with `torch.Tensor` type and file-like objects)
# please file a feature request.
#

######################################################################
# 2. Preparation
# --------------
#

######################################################################
#
# .. note::
#
#    The streaming API requires FFmpeg libraries (>=4.1).
#
#    If you are using Anaconda Python distribution,
#    ``conda install -c anaconda ffmpeg`` will install
#    the required libraries.
#
#    When running this tutorial in Google Colab, the following
#    command should do.
#
#    .. code::
#
#       !add-apt-repository -y ppa:savoury1/ffmpeg4
#       !apt-get -qq install -y ffmpeg

import IPython
import matplotlib.pyplot as plt
import torch
import torchaudio
from torchaudio.prototype.io import Streamer

print(torch.__version__)
print(torchaudio.__version__)

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"

######################################################################
# 3. Opening the source
# ---------------------
#
# There are mainly three different sources that streaming API can
# handle. Whichever source is used, the remaining processes
# (configuring the output, applying preprocessing) are same.
#
# 1. Common media formats
# 2. Audio / Video devices
# 3. Synthetic audio / video sources
#
# The following section covers how to open common media formats.
# For the other streams, please refer to the
# `Advanced I/O streams` section.
#

######################################################################
#
# To open a media file, you can simply pass the path of the file to
# the constructor of `Streamer`.
#
# .. code::
#
#    Streamer(src="audio.wav")
#
#    Streamer(src="audio.mp3")
#
# This works for image file, video file and video streams.
#
# .. code::
#
#    # Still image
#    Streamer(src="image.jpeg")
#
#    # Video file
#    Streamer(src="video.mpeg")
#
#    # Video on remote server
#    Streamer(src="https://example.com/video.mp4")
#
#    # Playlist format
#    Streamer(src="https://example.com/playlist.m3u")
#
# If attempting to load headerless raw data, you can use ``format`` and
# ``option`` to specify the format of the data.
#
# Say, you converted an audio file into faw format with ``sox`` command
# as follow;
#
# .. code::
#
#    # Headerless, 16-bit signed integer PCM, resampled at 16k Hz.
#    $ sox original.wav -r 16000 raw.s2
#
# Such audio can be opened like following.
#
# .. code::
#
#    Streamer(src="raw.s2", format="s16le", option={"sample_rate": "16000"})
#

######################################################################
# 4. Checking the source streams
# ------------------------------
#
# Once the media is opened, we can inspect the streams and configure
# the output streams.
#
# You can check the number of source streams with
# :py:attr:`~torchaudio.prototype.io.Streamer.num_src_streams`.
#
# .. note::
#    The number of streams is NOT the number of channels.
#    Each audio stream can contain an arbitrary number of channels.
#
# To check the metadata of source stream you can use
# :py:meth:`~torchaudio.prototype.io.Streamer.get_src_stream_info`
# method and provide the index of the source stream.
#
# This method returns
# :py:class:`~torchaudio.prototype.io.SourceStream`. If a source
# stream is audio type, then the return type is
# :py:class:`~torchaudio.prototype.io.SourceAudioStream`, which is
# a subclass of `SourceStream`, with additional audio-specific attributes.
# Similarly, if a source stream is video type, then the return type is
# :py:class:`~torchaudio.prototype.io.SourceVideoStream`.

######################################################################
# For regular audio formats and still image formats, such as `WAV`
# and `JPEG`, the number of souorce streams is 1.
#

streamer = Streamer(AUDIO_URL)
print("The number of source streams:", streamer.num_src_streams)
print(streamer.get_src_stream_info(0))

######################################################################
# Container formats and playlist formats may contain multiple streams
# of different media type.
#

src = "https://devstreaming-cdn.apple.com/videos/streaming/examples/img_bipbop_adv_example_fmp4/master.m3u8"
streamer = Streamer(src)
print("The number of source streams:", streamer.num_src_streams)
for i in range(streamer.num_src_streams):
    print(streamer.get_src_stream_info(i))

######################################################################
# 5. Configuring output streams
# -------------------------------
#
# The stream API lets you stream data from an arbitrary combination of
# the input streams. If your application does not need audio or video,
# you can omit them. Or if you want to apply different preprocessing
# to the same source stream, you can duplicate the source stream.
#

######################################################################
# 5.1. Default streams
# --------------------
#
# When there are multiple streams in the source, it is not immediately
# clear which stream should be used.
#
# FFmpeg implements some heuristics to determine the default stream.
# The resulting stream index is exposed via
#
# :py:attr:`~torchaudio.prototype.io.Streamer.default_audio_stream` and
# :py:attr:`~torchaudio.prototype.io.Streamer.default_video_stream`.
#

######################################################################
# 5.2. Configuring output streams
# -------------------------------
#
# Once you know which source stream you want to use, then you can
# configure output streams with
# :py:meth:`~torchaudio.prototype.io.Streamer.add_basic_audio_stream` and
# :py:meth:`~torchaudio.prototype.io.Streamer.add_basic_video_stream`.
#
# These methods provide a simple way to change the basic property of
# media to match the application's requirements.
#
# The arguments common to both methods are;
#
# - ``frames_per_chunk``: How many frames at maximum should be
#   returned at each iteration.
#   For audio, the resulting tensor will be the shape of
#   `(frames_per_chunk, num_channels)`.
#   For video, it will be
#   `(frames_per_chunk, num_channels, height, width)`.
# - ``buffer_chunk_size``: The maximum number of chunks to be buffered internally.
#   When the Streamer buffered this number of chunks and is asked to pull
#   more frames, Streamer drops the old frames/chunks.
# - ``stream_index``: The index of the source stream.
#
# For audio output stream, you can provide the following additional
# parameters to change the audio properties.
#
# - ``sample_rate``: When provided, Streamer resamples the audio on-the-fly.
# - ``dtype``: By default the Streamer returns tensor of `float32` dtype,
#   with sample values ranging `[-1, 1]`. By providing ``dtype`` argument
#   the resulting dtype and value range is changed.
#
# For video output stream, the following parameters are available.
#
# - ``frame_rate``: Change the frame rate by dropping or duplicating
#   frames. No interpolation is performed.
# - ``width``, ``height``: Change the image size.
# - ``format``: Change the image format.
#

######################################################################
#
# .. code::
#
#    streamer = Streamer(...)
#
#    # Stream audio from default audio source stream
#    # 256 frames at a time, keeping the original sampling rate.
#    streamer.add_basic_audio_stream(
#        frames_per_chunk=256,
#    )
#
#    # Stream audio from source stream `i`.
#    # Resample audio to 8k Hz, stream 256 frames at each
#    streamer.add_basic_audio_stream(
#        frames_per_chunk=256,
#        stream_index=i,
#        sample_rate=8000,
#    )
#

######################################################################
#
# .. code::
#
#    # Stream video from default video source stream.
#    # 10 frames at a time, at 30 FPS
#    # RGB color channels.
#    streamer.add_basic_video_stream(
#        frames_per_chunk=10,
#        frame_rate=30,
#        format="RGB"
#    )
#
#    # Stream video from source stream `j`,
#    # 10 frames at a time, at 30 FPS
#    # BGR color channels with rescaling to 128x128
#    streamer.add_basic_video_stream(
#        frames_per_chunk=10,
#        stream_index=j,
#        frame_rate=30,
#        width=128,
#        height=128,
#        format="BGR"
#    )
#

######################################################################
#
# You can check the resulting output streams in a similar manner as
# checking the source streams.
# :py:attr:`~torchaudio.prototype.io.Streamer.num_out_streams` reports
# the number of configured output streams, and
# :py:meth:`~torchaudio.prototype.io.Streamer.get_out_stream_info`
# fetches the information about the output streams.
#
# .. code::
#
#    for i in range(streamer.num_out_streams):
#        print(streamer.get_out_stream_info(i))
#

######################################################################
#
# If you want to remove an output stream, you can do so with
# :py:meth:`~torchaudio.prototype.io.Streamer.remove_stream` method.
#
# .. code::
#
#    # Removes the first output stream.
#    streamer.remove_stream(0)
#

######################################################################
# 5.3. Streaming
# --------------
#
# To stream media data, the streamer alternates the process of
# fetching and decoding the source data, and passing the resulting
# audio / video data to client code.
#
# There are low-level methods that performs these operations.
# :py:meth:`~torchaudio.prototype.io.Streamer.is_buffer_ready`,
# :py:meth:`~torchaudio.prototype.io.Streamer.process_packet` and
# :py:meth:`~torchaudio.prototype.io.Streamer.pop_chunks`.
#
# In this tutorial, we will use the high-level API, iterator protocol.
# It is as simple as a ``for`` loop.
#
# .. code::
#
#    streamer = Streamer(...)
#    streamer.add_basic_audio_stream(...)
#    streamer.add_basic_video_stream(...)
#
#    for chunks in streamer.stream():
#        audio_chunk, video_chunk = chunks
#        ...
#

######################################################################
# 6. Example
# ----------
#
# Let's take an example video to configure the output streams.
# We will use the following video.
#
# .. raw:: html
#
#    <iframe width="560" height="315"
#     src="https://www.youtube.com/embed/6zNsc0e3Zns"
#     title="YouTube video player"
#     frameborder="0"
#     allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture"
#     allowfullscreen></iframe>
#
# Source: https://svs.gsfc.nasa.gov/13013 (This video is in public domain)
#
# Credit: NASA's Goddard Space Flight Center.
#
# NASA's Media Usage Guidelines: https://www.nasa.gov/multimedia/guidelines/index.html
#
#

######################################################################
#
# 6.1. Opening the source media
# ------------------------------
# Firstly, let's list the available streams and its properties.
#

streamer = Streamer(VIDEO_URL)
for i in range(streamer.num_src_streams):
    print(streamer.get_src_stream_info(i))

######################################################################
#
# Now we configure the output stream.
#
# 6.2. Configuring ouptut streams
# -------------------------------

# fmt: off
# Audio stream with 8k Hz
streamer.add_basic_audio_stream(
    frames_per_chunk=8000,
    sample_rate=8000,
)

# Audio stream with 16k Hz
streamer.add_basic_audio_stream(
    frames_per_chunk=16000,
    sample_rate=16000,
)

# Video stream with 960x540 at 1 FPS.
streamer.add_basic_video_stream(
    frames_per_chunk=1,
    frame_rate=1,
    width=960,
    height=540,
    format="RGB",
)

# Video stream with 320x320 (stretched) at 3 FPS, grayscale
streamer.add_basic_video_stream(
    frames_per_chunk=3,
    frame_rate=3,
    width=320,
    height=320,
    format="GRAY",
)
# fmt: on

######################################################################
# .. note::
#
#    When configuring multiple output streams, in order to keep all
#    streams synced, set parameters so that the ratio between
#    ``frames_per_chunk`` and ``sample_rate`` or ``frame_rate`` is
#    consistent across output streams.
#

######################################################################
# Checking the output streams.
#

for i in range(streamer.num_out_streams):
    print(streamer.get_out_stream_info(i))

######################################################################
# Remove the second audio stream.
#

streamer.remove_stream(1)
for i in range(streamer.num_out_streams):
    print(streamer.get_out_stream_info(i))

######################################################################
# 6.3. Streaming
# --------------
#

######################################################################
# Jump to the 10 second point.
#
streamer.seek(10.0)

######################################################################
#
# Now, let's finally iterate over the output streams.
#

n_ite = 3
waveforms, vids1, vids2 = [], [], []
for i, (waveform, vid1, vid2) in enumerate(streamer.stream()):
    waveforms.append(waveform)
    vids1.append(vid1)
    vids2.append(vid2)
    if i + 1 == n_ite:
        break

######################################################################
# For audio stream, the chunk Tensor will be the shape of
# `(frames_per_chunk, num_channels)`, and for video stream,
# it is `(frames_per_chunk, num_color_channels, height, width)`.
#

print(waveforms[0].shape)
print(vids1[0].shape)
print(vids2[0].shape)

######################################################################
# Let's visualize what we received.

k = 3
fig = plt.figure()
gs = fig.add_gridspec(3, k * n_ite)
for i, waveform in enumerate(waveforms):
    ax = fig.add_subplot(gs[0, k * i : k * (i + 1)])
    ax.specgram(waveform[:, 0], Fs=8000)
    ax.set_yticks([])
    ax.set_xticks([])
    ax.set_title(f"Iteration {i}")
    if i == 0:
        ax.set_ylabel("Stream 0")
for i, vid in enumerate(vids1):
    ax = fig.add_subplot(gs[1, k * i : k * (i + 1)])
    ax.imshow(vid[0].permute(1, 2, 0))  # NCHW->HWC
    ax.set_yticks([])
    ax.set_xticks([])
    if i == 0:
        ax.set_ylabel("Stream 1")
for i, vid in enumerate(vids2):
    for j in range(3):
        ax = fig.add_subplot(gs[2, k * i + j : k * i + j + 1])
        ax.imshow(vid[j].permute(1, 2, 0), cmap="gray")
        ax.set_yticks([])
        ax.set_xticks([])
        if i == 0 and j == 0:
            ax.set_ylabel("Stream 2")
plt.tight_layout()
plt.show(block=False)

######################################################################
# [Advanced I/O streams]
# ----------------------
#

######################################################################
# 1. 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.
#
# .. code::
#
#    $ 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.
#
# .. code::
#
#    >>> Streamer(
#    ...     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.
#
# .. code::
#
#    >>> streamer = Streamer(
#    ...     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)
#

######################################################################
# 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
#

######################################################################
# 2.1. Synthetic audio examples
# -----------------------------
#

######################################################################
# Sine wave with
# ~~~~~~~~~~~~~~
#
# https://ffmpeg.org/ffmpeg-filters.html#sine
#
# .. code::
#
#    Streamer(src="sine=sample_rate=8000:frequency=360", format="lavfi")
#
# .. raw:: html
#
#    <audio controls>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/sine.wav">
#    </audio>
#    <img
#     src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/sine.png"
#     class="sphx-glr-single-img" style="width:80%">
#

######################################################################
# Generate an audio signal specified by an expression
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# https://ffmpeg.org/ffmpeg-filters.html#aevalsrc
#
# .. code::
#
#    # 5 Hz binaural beats on a 360 Hz carrier
#    Streamer(
#        src=(
#            'aevalsrc='
#            'sample_rate=8000:'
#            'exprs=0.1*sin(2*PI*(360-5/2)*t)|0.1*sin(2*PI*(360+5/2)*t)'
#        ),
#        format='lavfi',
#     )
#
# .. raw:: html
#
#    <audio controls>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/aevalsrc.wav">
#    </audio>
#    <img
#     src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/aevalsrc.png"
#     class="sphx-glr-single-img" style="width:80%">
#

######################################################################
# Generate noise with
# ~~~~~~~~~~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#anoisesrc
#
# .. code::
#
#    Streamer(src="anoisesrc=color=pink:sample_rate=8000:amplitude=0.5", format="lavfi")
#
# .. raw:: html
#
#    <audio controls>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/anoisesrc.wav">
#    </audio>
#    <img
#     src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/anoisesrc.png"
#     class="sphx-glr-single-img" style="width:80%">
#

######################################################################
# 2.2. Synthetic video examples
# -----------------------------
#

######################################################################
# Cellular automaton
# ~~~~~~~~~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#cellauto
#
# .. code::
#
#    Streamer(src=f"cellauto", format="lavfi")
#
# .. raw:: html
#
#    <video controls autoplay loop muted>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/cellauto.mp4">
#    </video>
#

######################################################################
# Mandelbrot
# ~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#cellauto
#
# .. code::
#
#    Streamer(src=f"mandelbrot", format="lavfi")
#
# .. raw:: html
#
#    <video controls autoplay loop muted>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/mandelbrot.mp4">
#    </video>
#

######################################################################
# MPlayer Test patterns
# ~~~~~~~~~~~~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#mptestsrc
#
# .. code::
#
#    Streamer(src=f"mptestsrc", format="lavfi")
#
# .. raw:: html
#
#    <video controls autoplay loop muted width=192 height=192>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/mptestsrc.mp4">
#    </video>
#

######################################################################
# John Conway's life game
# ~~~~~~~~~~~~~~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#life
#
# .. code::
#
#    Streamer(src=f"life", format="lavfi")
#
# .. raw:: html
#
#    <video controls autoplay loop muted>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/life.mp4">
#    </video>
#

######################################################################
# Sierpinski carpet/triangle fractal
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# https://ffmpeg.org/ffmpeg-filters.html#sierpinski
#
# .. code::
#
#    Streamer(src=f"sierpinski", format="lavfi")
#
# .. raw:: html
#
#    <video controls autoplay loop muted>
#        <source src="https://download.pytorch.org/torchaudio/tutorial-assets/stream-api/sierpinski.mp4">
#    </video>
#

######################################################################
# 3. Custom output streams
# ------------------------
#
# When defining an output stream, you can use
# :py:meth:`~torchaudio.prototype.io.Streamer.add_audio_stream` and
# :py:meth:`~torchaudio.prototype.io.Streamer.add_video_stream` methods.
#
# These methods take ``filter_desc`` argument, which is a string
# formatted according to ffmpeg's
# `filter expression <https://ffmpeg.org/ffmpeg-filters.html>`_.
#
# 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``.
#
# .. note::
#
#    - 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.
#

######################################################################
# 3.1. Custom audio streams
# -------------------------
#
#

# fmt: off
descs = [
    # No filtering
    "anull",
    # Apply a highpass filter then a lowpass filter
    "highpass=f=200,lowpass=f=1000",
    # Manipulate spectrogram
    (
        "afftfilt="
        "real='hypot(re,im)*sin(0)':"
        "imag='hypot(re,im)*cos(0)':"
        "win_size=512:"
        "overlap=0.75"
    ),
    # Manipulate spectrogram
    (
        "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"
    ),
]
# fmt: on

######################################################################
#

sample_rate = 8000

streamer = Streamer(AUDIO_URL)
for desc in descs:
    streamer.add_audio_stream(
        frames_per_chunk=40000,
        filter_desc=f"aresample={sample_rate},{desc},aformat=sample_fmts=fltp",
    )

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].plot(waveform)
    axs[0].grid(True)
    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)


######################################################################
# Original
# ~~~~~~~~
#

_display(0)

######################################################################
# Highpass / lowpass filter
# ~~~~~~~~~~~~~~~~~~~~~~~~~
#

_display(1)

######################################################################
# FFT filter - Robot 🤖
# ~~~~~~~~~~~~~~~~~~~~~
#

_display(2)

######################################################################
# FFT filter - Whisper
# ~~~~~~~~~~~~~~~~~~~~
#

_display(3)

######################################################################
# 3.2. Custom video streams
# -------------------------
#

# fmt: off
descs = [
    # No effect
    "null",
    # 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
    "edgedetect=mode=canny",
    # Rotate image by randomly and fill the background with brown
    "rotate=angle=-random(1)*PI:fillcolor=brown",
    # Manipulate pixel values based on the coordinate
    "geq=r='X/W*r(X,Y)':g='(1-X/W)*g(X,Y)':b='(H-Y)/H*b(X,Y)'"
]
# fmt: on

######################################################################
#

streamer = Streamer(VIDEO_URL)
for desc in descs:
    streamer.add_video_stream(
        frames_per_chunk=30,
        filter_desc=f"fps=10,{desc},format=pix_fmts=rgb24",
    )

streamer.seek(12)

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))
        axs[j].set_axis_off()
    plt.tight_layout()
    plt.show(block=False)


######################################################################
# Original
# ~~~~~~~~

_display(0)

######################################################################
# Mirror
# ~~~~~~

_display(1)

######################################################################
# Edge detection
# ~~~~~~~~~~~~~~~

_display(2)

######################################################################
# Random rotation
# ~~~~~~~~~~~~~~~

_display(3)

######################################################################
# Pixel manipulation
# ~~~~~~~~~~~~~~~~~~

_display(4)