File: video_reader.cpp

package info (click to toggle)
pytorch-vision 0.21.0-3
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 20,228 kB
  • sloc: python: 65,904; cpp: 11,406; ansic: 2,459; java: 550; sh: 265; xml: 79; objc: 56; makefile: 33
file content (677 lines) | stat: -rw-r--r-- 22,192 bytes parent folder | download
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
#include "video_reader.h"

#include "../decoder/memory_buffer.h"
#include "../decoder/sync_decoder.h"

// If we are in a Windows environment, we need to define
// initialization functions for the _custom_ops extension
#ifdef _WIN32
void* PyInit_video_reader(void) {
  return nullptr;
}
#endif

using namespace ffmpeg;

namespace vision {
namespace video_reader {

namespace {

const AVPixelFormat defaultVideoPixelFormat = AV_PIX_FMT_RGB24;
const AVSampleFormat defaultAudioSampleFormat = AV_SAMPLE_FMT_FLT;
const AVRational timeBaseQ = AVRational{1, AV_TIME_BASE};
const size_t decoderTimeoutMs = 600000;
// A jitter can be added to the end of the range to avoid conversion/rounding
// error, small value 100us won't be enough to select the next frame, but enough
// to compensate rounding error due to the multiple conversions.
const size_t timeBaseJitterUs = 100;

DecoderParameters getDecoderParams(
    int64_t videoStartUs,
    int64_t videoEndUs,
    double seekFrameMarginUs,
    int64_t getPtsOnly,
    int64_t readVideoStream,
    int videoWidth,
    int videoHeight,
    int videoMinDimension,
    int videoMaxDimension,
    int64_t readAudioStream,
    int audioSamples,
    int audioChannels) {
  DecoderParameters params;
  params.headerOnly = getPtsOnly != 0;
  params.seekAccuracy = seekFrameMarginUs;
  params.startOffset = videoStartUs;
  params.endOffset = videoEndUs;
  params.timeoutMs = decoderTimeoutMs;
  params.preventStaleness = false;

  if (readVideoStream == 1) {
    MediaFormat videoFormat(0);
    videoFormat.type = TYPE_VIDEO;
    videoFormat.format.video.format = defaultVideoPixelFormat;
    videoFormat.format.video.width = videoWidth;
    videoFormat.format.video.height = videoHeight;
    videoFormat.format.video.minDimension = videoMinDimension;
    videoFormat.format.video.maxDimension = videoMaxDimension;
    params.formats.insert(videoFormat);
  }

  if (readAudioStream == 1) {
    MediaFormat audioFormat;
    audioFormat.type = TYPE_AUDIO;
    audioFormat.format.audio.format = defaultAudioSampleFormat;
    audioFormat.format.audio.samples = audioSamples;
    audioFormat.format.audio.channels = audioChannels;
    params.formats.insert(audioFormat);
  }

  return params;
}

// returns number of written bytes
template <typename T>
size_t fillTensor(
    std::vector<DecoderOutputMessage>& msgs,
    torch::Tensor& frame,
    torch::Tensor& framePts,
    int64_t num,
    int64_t den) {
  if (msgs.empty()) {
    return 0;
  }
  T* frameData = frame.numel() > 0 ? frame.data_ptr<T>() : nullptr;
  int64_t* framePtsData = framePts.data_ptr<int64_t>();
  TORCH_CHECK_EQ(framePts.size(0), (int64_t)msgs.size());
  size_t avgElementsInFrame = frame.numel() / msgs.size();

  size_t offset = 0;
  for (size_t i = 0; i < msgs.size(); ++i) {
    const auto& msg = msgs[i];
    // convert pts into original time_base
    AVRational avr = AVRational{(int)num, (int)den};
    framePtsData[i] = av_rescale_q(msg.header.pts, timeBaseQ, avr);
    VLOG(2) << "PTS type: " << sizeof(T) << ", us: " << msg.header.pts
            << ", original: " << framePtsData[i];

    if (frameData) {
      auto sizeInBytes = msg.payload->length();
      memcpy(frameData + offset, msg.payload->data(), sizeInBytes);
      if (sizeof(T) == sizeof(uint8_t)) {
        // Video - move by allocated frame size
        offset += avgElementsInFrame / sizeof(T);
      } else {
        // Audio - move by number of samples
        offset += sizeInBytes / sizeof(T);
      }
    }
  }
  return offset * sizeof(T);
}

size_t fillVideoTensor(
    std::vector<DecoderOutputMessage>& msgs,
    torch::Tensor& videoFrame,
    torch::Tensor& videoFramePts,
    int64_t num,
    int64_t den) {
  return fillTensor<uint8_t>(msgs, videoFrame, videoFramePts, num, den);
}

size_t fillAudioTensor(
    std::vector<DecoderOutputMessage>& msgs,
    torch::Tensor& audioFrame,
    torch::Tensor& audioFramePts,
    int64_t num,
    int64_t den) {
  return fillTensor<float>(msgs, audioFrame, audioFramePts, num, den);
}

void offsetsToUs(
    double& seekFrameMargin,
    int64_t readVideoStream,
    int64_t videoStartPts,
    int64_t videoEndPts,
    int64_t videoTimeBaseNum,
    int64_t videoTimeBaseDen,
    int64_t readAudioStream,
    int64_t audioStartPts,
    int64_t audioEndPts,
    int64_t audioTimeBaseNum,
    int64_t audioTimeBaseDen,
    int64_t& videoStartUs,
    int64_t& videoEndUs) {
  seekFrameMargin *= AV_TIME_BASE;
  videoStartUs = 0;
  videoEndUs = -1;

  if (readVideoStream) {
    AVRational vr = AVRational{(int)videoTimeBaseNum, (int)videoTimeBaseDen};
    if (videoStartPts > 0) {
      videoStartUs = av_rescale_q(videoStartPts, vr, timeBaseQ);
    }
    if (videoEndPts > 0) {
      // Add jitter to the end of the range to avoid conversion/rounding error.
      // Small value 100us won't be enough to select the next frame, but enough
      // to compensate rounding error due to the multiple conversions.
      videoEndUs = timeBaseJitterUs + av_rescale_q(videoEndPts, vr, timeBaseQ);
    }
  } else if (readAudioStream) {
    AVRational ar = AVRational{(int)audioTimeBaseNum, (int)audioTimeBaseDen};
    if (audioStartPts > 0) {
      videoStartUs = av_rescale_q(audioStartPts, ar, timeBaseQ);
    }
    if (audioEndPts > 0) {
      // Add jitter to the end of the range to avoid conversion/rounding error.
      // Small value 100us won't be enough to select the next frame, but enough
      // to compensate rounding error due to the multiple conversions.
      videoEndUs = timeBaseJitterUs + av_rescale_q(audioEndPts, ar, timeBaseQ);
    }
  }
}

torch::List<torch::Tensor> readVideo(
    bool isReadFile,
    const torch::Tensor& input_video,
    std::string videoPath,
    double seekFrameMargin,
    int64_t getPtsOnly,
    int64_t readVideoStream,
    int64_t width,
    int64_t height,
    int64_t minDimension,
    int64_t maxDimension,
    int64_t videoStartPts,
    int64_t videoEndPts,
    int64_t videoTimeBaseNum,
    int64_t videoTimeBaseDen,
    int64_t readAudioStream,
    int64_t audioSamples,
    int64_t audioChannels,
    int64_t audioStartPts,
    int64_t audioEndPts,
    int64_t audioTimeBaseNum,
    int64_t audioTimeBaseDen) {
  int64_t videoStartUs, videoEndUs;

  offsetsToUs(
      seekFrameMargin,
      readVideoStream,
      videoStartPts,
      videoEndPts,
      videoTimeBaseNum,
      videoTimeBaseDen,
      readAudioStream,
      audioStartPts,
      audioEndPts,
      audioTimeBaseNum,
      audioTimeBaseDen,
      videoStartUs,
      videoEndUs);

  DecoderParameters params = getDecoderParams(
      videoStartUs, // videoStartPts
      videoEndUs, // videoEndPts
      seekFrameMargin, // seekFrameMargin
      getPtsOnly, // getPtsOnly
      readVideoStream, // readVideoStream
      width, // width
      height, // height
      minDimension, // minDimension
      maxDimension, // maxDimension
      readAudioStream, // readAudioStream
      audioSamples, // audioSamples
      audioChannels // audioChannels
  );

  SyncDecoder decoder;
  std::vector<DecoderOutputMessage> audioMessages, videoMessages;
  DecoderInCallback callback = nullptr;
  std::string logMessage, logType;
  if (isReadFile) {
    params.uri = videoPath;
    logType = "file";
    logMessage = videoPath;
  } else {
    callback = MemoryBuffer::getCallback(
        input_video.data_ptr<uint8_t>(), input_video.size(0));
    logType = "memory";
    logMessage = std::to_string(input_video.size(0));
  }

  VLOG(1) << "Video decoding from " << logType << " [" << logMessage
          << "] has started";

  const auto now = std::chrono::system_clock::now();

  bool succeeded;
  DecoderMetadata audioMetadata, videoMetadata;
  std::vector<DecoderMetadata> metadata;
  if ((succeeded = decoder.init(params, std::move(callback), &metadata))) {
    for (const auto& header : metadata) {
      if (header.format.type == TYPE_VIDEO) {
        videoMetadata = header;
      } else if (header.format.type == TYPE_AUDIO) {
        audioMetadata = header;
      }
    }
    int res;
    DecoderOutputMessage msg;
    while (0 == (res = decoder.decode(&msg, decoderTimeoutMs))) {
      if (msg.header.format.type == TYPE_VIDEO) {
        videoMessages.push_back(std::move(msg));
      }
      if (msg.header.format.type == TYPE_AUDIO) {
        audioMessages.push_back(std::move(msg));
      }
      msg.payload.reset();
    }
  } else {
    LOG(ERROR) << "Decoder initialization has failed";
  }
  const auto then = std::chrono::system_clock::now();
  VLOG(1) << "Video decoding from " << logType << " [" << logMessage
          << "] has finished, "
          << std::chrono::duration_cast<std::chrono::microseconds>(then - now)
                 .count()
          << " us";

  decoder.shutdown();

  // video section
  torch::Tensor videoFrame = torch::zeros({0}, torch::kByte);
  torch::Tensor videoFramePts = torch::zeros({0}, torch::kLong);
  torch::Tensor videoTimeBase = torch::zeros({0}, torch::kInt);
  torch::Tensor videoFps = torch::zeros({0}, torch::kFloat);
  torch::Tensor videoDuration = torch::zeros({0}, torch::kLong);

  if (succeeded && readVideoStream == 1) {
    if (!videoMessages.empty()) {
      const auto& header = videoMetadata;
      const auto& format = header.format.format.video;
      int numVideoFrames = videoMessages.size();
      int outHeight = format.height;
      int outWidth = format.width;
      int numChannels = 3; // decoder guarantees the default AV_PIX_FMT_RGB24

      size_t expectedWrittenBytes = 0;
      if (getPtsOnly == 0) {
        videoFrame = torch::zeros(
            {numVideoFrames, outHeight, outWidth, numChannels}, torch::kByte);
        expectedWrittenBytes =
            (size_t)numVideoFrames * outHeight * outWidth * numChannels;
      }

      videoFramePts = torch::zeros({numVideoFrames}, torch::kLong);

      VLOG(2) << "video duration: " << header.duration
              << ", fps: " << header.fps << ", num: " << header.num
              << ", den: " << header.den << ", num frames: " << numVideoFrames;

      auto numberWrittenBytes = fillVideoTensor(
          videoMessages, videoFrame, videoFramePts, header.num, header.den);

      TORCH_CHECK_EQ(numberWrittenBytes, expectedWrittenBytes);

      videoTimeBase = torch::zeros({2}, torch::kInt);
      int* videoTimeBaseData = videoTimeBase.data_ptr<int>();
      videoTimeBaseData[0] = header.num;
      videoTimeBaseData[1] = header.den;

      videoFps = torch::zeros({1}, torch::kFloat);
      float* videoFpsData = videoFps.data_ptr<float>();
      videoFpsData[0] = header.fps;

      videoDuration = torch::zeros({1}, torch::kLong);
      int64_t* videoDurationData = videoDuration.data_ptr<int64_t>();
      AVRational vr = AVRational{(int)header.num, (int)header.den};
      videoDurationData[0] = av_rescale_q(header.duration, timeBaseQ, vr);
      VLOG(1) << "Video decoding from " << logType << " [" << logMessage
              << "] filled video tensors";
    } else {
      VLOG(1) << "Miss video stream";
    }
  }

  // audio section
  torch::Tensor audioFrame = torch::zeros({0}, torch::kFloat);
  torch::Tensor audioFramePts = torch::zeros({0}, torch::kLong);
  torch::Tensor audioTimeBase = torch::zeros({0}, torch::kInt);
  torch::Tensor audioSampleRate = torch::zeros({0}, torch::kInt);
  torch::Tensor audioDuration = torch::zeros({0}, torch::kLong);
  if (succeeded && readAudioStream == 1) {
    if (!audioMessages.empty()) {
      const auto& header = audioMetadata;
      const auto& format = header.format.format.audio;

      int64_t outAudioChannels = format.channels;
      int bytesPerSample =
          av_get_bytes_per_sample(static_cast<AVSampleFormat>(format.format));

      int numAudioFrames = audioMessages.size();
      int64_t numAudioSamples = 0;
      if (getPtsOnly == 0) {
        int64_t frameSizeTotal = 0;
        for (auto const& audioMessage : audioMessages) {
          frameSizeTotal += audioMessage.payload->length();
        }

        TORCH_CHECK_EQ(frameSizeTotal % (outAudioChannels * bytesPerSample), 0);
        numAudioSamples = frameSizeTotal / (outAudioChannels * bytesPerSample);

        audioFrame =
            torch::zeros({numAudioSamples, outAudioChannels}, torch::kFloat);
      }
      audioFramePts = torch::zeros({numAudioFrames}, torch::kLong);

      VLOG(2) << "audio duration: " << header.duration
              << ", channels: " << format.channels
              << ", sample rate: " << format.samples << ", num: " << header.num
              << ", den: " << header.den;

      auto numberWrittenBytes = fillAudioTensor(
          audioMessages, audioFrame, audioFramePts, header.num, header.den);
      TORCH_CHECK_EQ(
          numberWrittenBytes,
          numAudioSamples * outAudioChannels * sizeof(float));

      audioTimeBase = torch::zeros({2}, torch::kInt);
      int* audioTimeBaseData = audioTimeBase.data_ptr<int>();
      audioTimeBaseData[0] = header.num;
      audioTimeBaseData[1] = header.den;

      audioSampleRate = torch::zeros({1}, torch::kInt);
      int* audioSampleRateData = audioSampleRate.data_ptr<int>();
      audioSampleRateData[0] = format.samples;

      audioDuration = torch::zeros({1}, torch::kLong);
      int64_t* audioDurationData = audioDuration.data_ptr<int64_t>();
      AVRational ar = AVRational{(int)header.num, (int)header.den};
      audioDurationData[0] = av_rescale_q(header.duration, timeBaseQ, ar);
      VLOG(1) << "Video decoding from " << logType << " [" << logMessage
              << "] filled audio tensors";
    } else {
      VLOG(1) << "Miss audio stream";
    }
  }

  torch::List<torch::Tensor> result;
  result.push_back(std::move(videoFrame));
  result.push_back(std::move(videoFramePts));
  result.push_back(std::move(videoTimeBase));
  result.push_back(std::move(videoFps));
  result.push_back(std::move(videoDuration));
  result.push_back(std::move(audioFrame));
  result.push_back(std::move(audioFramePts));
  result.push_back(std::move(audioTimeBase));
  result.push_back(std::move(audioSampleRate));
  result.push_back(std::move(audioDuration));

  VLOG(1) << "Video decoding from " << logType << " [" << logMessage
          << "] about to return";

  return result;
}

torch::List<torch::Tensor> probeVideo(
    bool isReadFile,
    const torch::Tensor& input_video,
    std::string videoPath) {
  DecoderParameters params = getDecoderParams(
      0, // videoStartUs
      -1, // videoEndUs
      0, // seekFrameMargin
      1, // getPtsOnly
      1, // readVideoStream
      0, // width
      0, // height
      0, // minDimension
      0, // maxDimension
      1, // readAudioStream
      0, // audioSamples
      0 // audioChannels
  );

  SyncDecoder decoder;
  DecoderInCallback callback = nullptr;
  std::string logMessage, logType;
  if (isReadFile) {
    params.uri = videoPath;
    logType = "file";
    logMessage = videoPath;
  } else {
    callback = MemoryBuffer::getCallback(
        input_video.data_ptr<uint8_t>(), input_video.size(0));
    logType = "memory";
    logMessage = std::to_string(input_video.size(0));
  }

  VLOG(1) << "Video probing from " << logType << " [" << logMessage
          << "] has started";

  const auto now = std::chrono::system_clock::now();

  bool succeeded;
  bool gotAudio = false, gotVideo = false;
  DecoderMetadata audioMetadata, videoMetadata;
  std::vector<DecoderMetadata> metadata;
  if ((succeeded = decoder.init(params, std::move(callback), &metadata))) {
    for (const auto& header : metadata) {
      if (header.format.type == TYPE_VIDEO) {
        gotVideo = true;
        videoMetadata = header;
      } else if (header.format.type == TYPE_AUDIO) {
        gotAudio = true;
        audioMetadata = header;
      }
    }
    const auto then = std::chrono::system_clock::now();
    VLOG(1) << "Video probing from " << logType << " [" << logMessage
            << "] has finished, "
            << std::chrono::duration_cast<std::chrono::microseconds>(then - now)
                   .count()
            << " us";
  } else {
    LOG(ERROR) << "Decoder initialization has failed";
  }

  decoder.shutdown();

  // video section
  torch::Tensor videoTimeBase = torch::zeros({0}, torch::kInt);
  torch::Tensor videoFps = torch::zeros({0}, torch::kFloat);
  torch::Tensor videoDuration = torch::zeros({0}, torch::kLong);

  if (succeeded && gotVideo) {
    videoTimeBase = torch::zeros({2}, torch::kInt);
    int* videoTimeBaseData = videoTimeBase.data_ptr<int>();
    const auto& header = videoMetadata;

    videoTimeBaseData[0] = header.num;
    videoTimeBaseData[1] = header.den;

    videoFps = torch::zeros({1}, torch::kFloat);
    float* videoFpsData = videoFps.data_ptr<float>();
    videoFpsData[0] = header.fps;

    videoDuration = torch::zeros({1}, torch::kLong);
    int64_t* videoDurationData = videoDuration.data_ptr<int64_t>();
    AVRational avr = AVRational{(int)header.num, (int)header.den};
    videoDurationData[0] = av_rescale_q(header.duration, timeBaseQ, avr);

    VLOG(2) << "Prob fps: " << header.fps << ", duration: " << header.duration
            << ", num: " << header.num << ", den: " << header.den;

    VLOG(1) << "Video probing from " << logType << " [" << logMessage
            << "] filled video tensors";
  } else {
    LOG(ERROR) << "Miss video stream";
  }

  // audio section
  torch::Tensor audioTimeBase = torch::zeros({0}, torch::kInt);
  torch::Tensor audioSampleRate = torch::zeros({0}, torch::kInt);
  torch::Tensor audioDuration = torch::zeros({0}, torch::kLong);

  if (succeeded && gotAudio) {
    audioTimeBase = torch::zeros({2}, torch::kInt);
    int* audioTimeBaseData = audioTimeBase.data_ptr<int>();
    const auto& header = audioMetadata;
    const auto& media = header.format;
    const auto& format = media.format.audio;

    audioTimeBaseData[0] = header.num;
    audioTimeBaseData[1] = header.den;

    audioSampleRate = torch::zeros({1}, torch::kInt);
    int* audioSampleRateData = audioSampleRate.data_ptr<int>();
    audioSampleRateData[0] = format.samples;

    audioDuration = torch::zeros({1}, torch::kLong);
    int64_t* audioDurationData = audioDuration.data_ptr<int64_t>();
    AVRational avr = AVRational{(int)header.num, (int)header.den};
    audioDurationData[0] = av_rescale_q(header.duration, timeBaseQ, avr);

    VLOG(2) << "Prob sample rate: " << format.samples
            << ", duration: " << header.duration << ", num: " << header.num
            << ", den: " << header.den;

    VLOG(1) << "Video probing from " << logType << " [" << logMessage
            << "] filled audio tensors";
  } else {
    VLOG(1) << "Miss audio stream";
  }

  torch::List<torch::Tensor> result;
  result.push_back(std::move(videoTimeBase));
  result.push_back(std::move(videoFps));
  result.push_back(std::move(videoDuration));
  result.push_back(std::move(audioTimeBase));
  result.push_back(std::move(audioSampleRate));
  result.push_back(std::move(audioDuration));

  VLOG(1) << "Video probing from " << logType << " [" << logMessage
          << "] is about to return";

  return result;
}

} // namespace

torch::List<torch::Tensor> read_video_from_memory(
    torch::Tensor input_video,
    double seekFrameMargin,
    int64_t getPtsOnly,
    int64_t readVideoStream,
    int64_t width,
    int64_t height,
    int64_t minDimension,
    int64_t maxDimension,
    int64_t videoStartPts,
    int64_t videoEndPts,
    int64_t videoTimeBaseNum,
    int64_t videoTimeBaseDen,
    int64_t readAudioStream,
    int64_t audioSamples,
    int64_t audioChannels,
    int64_t audioStartPts,
    int64_t audioEndPts,
    int64_t audioTimeBaseNum,
    int64_t audioTimeBaseDen) {
  C10_LOG_API_USAGE_ONCE(
      "torchvision.csrc.io.video_reader.video_reader.read_video_from_memory");
  return readVideo(
      false,
      input_video,
      "", // videoPath
      seekFrameMargin,
      getPtsOnly,
      readVideoStream,
      width,
      height,
      minDimension,
      maxDimension,
      videoStartPts,
      videoEndPts,
      videoTimeBaseNum,
      videoTimeBaseDen,
      readAudioStream,
      audioSamples,
      audioChannels,
      audioStartPts,
      audioEndPts,
      audioTimeBaseNum,
      audioTimeBaseDen);
}

torch::List<torch::Tensor> read_video_from_file(
    std::string videoPath,
    double seekFrameMargin,
    int64_t getPtsOnly,
    int64_t readVideoStream,
    int64_t width,
    int64_t height,
    int64_t minDimension,
    int64_t maxDimension,
    int64_t videoStartPts,
    int64_t videoEndPts,
    int64_t videoTimeBaseNum,
    int64_t videoTimeBaseDen,
    int64_t readAudioStream,
    int64_t audioSamples,
    int64_t audioChannels,
    int64_t audioStartPts,
    int64_t audioEndPts,
    int64_t audioTimeBaseNum,
    int64_t audioTimeBaseDen) {
  C10_LOG_API_USAGE_ONCE(
      "torchvision.csrc.io.video_reader.video_reader.read_video_from_file");
  torch::Tensor dummy_input_video = torch::ones({0});
  return readVideo(
      true,
      dummy_input_video,
      videoPath,
      seekFrameMargin,
      getPtsOnly,
      readVideoStream,
      width,
      height,
      minDimension,
      maxDimension,
      videoStartPts,
      videoEndPts,
      videoTimeBaseNum,
      videoTimeBaseDen,
      readAudioStream,
      audioSamples,
      audioChannels,
      audioStartPts,
      audioEndPts,
      audioTimeBaseNum,
      audioTimeBaseDen);
}

torch::List<torch::Tensor> probe_video_from_memory(torch::Tensor input_video) {
  C10_LOG_API_USAGE_ONCE(
      "torchvision.csrc.io.video_reader.video_reader.probe_video_from_memory");
  return probeVideo(false, input_video, "");
}

torch::List<torch::Tensor> probe_video_from_file(std::string videoPath) {
  C10_LOG_API_USAGE_ONCE(
      "torchvision.csrc.io.video_reader.video_reader.probe_video_from_file");
  torch::Tensor dummy_input_video = torch::ones({0});
  return probeVideo(true, dummy_input_video, videoPath);
}

TORCH_LIBRARY_FRAGMENT(video_reader, m) {
  m.def("read_video_from_memory", read_video_from_memory);
  m.def("read_video_from_file", read_video_from_file);
  m.def("probe_video_from_memory", probe_video_from_memory);
  m.def("probe_video_from_file", probe_video_from_file);
}

} // namespace video_reader
} // namespace vision