Video tutorial-FFmpeg video player development-C/C++ Subscribe now After subscription: Click here to watch the video course join () if _name_ = '_main_' : main ( device = 'avfoundation', src = ':1', bundle = torchaudio. Process ( target = stream, args = ( q, device, src, segment_length, sample_rate )) p. infer ( segment ) print ( transcript, end = '', flush = True ) import torch.multiprocessing as mp ctx = mp. get () segment = cacher ( chunk ) transcript = pipeline. inference_mode () def infer (): for _ in range ( NUM_ITER ): chunk = q. hop_length print ( f 'Sample rate: seconds)' ) cacher = ContextCacher ( segment_length, context_length ). _version_ ) print ( 'Building pipeline.' ) pipeline = Pipeline ( bundle ) sample_rate = bundle. Timeout and backoff parameters allow client code to control theįor the detail of timeout and backoff parameters, please referĭef main ( device, src, bundle ): print ( torch. Reporting this errorįrom low-level implementation all the way back to Python layer,įor this reason, the retry behavior is implemented in C++ layer, and Precise timing is the key for smooth streaming. The underlying implementation reports special error code, and expects Than that at which the hardware can prepare the data, then When acquiring data, if the rate of acquisition requests is higher We provide timeout and backoff parameters to stream method. The notable difference from the non-device streaming is that, stream ( timeout =- 1, backoff = 1.0 ) for _ in range ( NUM_ITER ): ( chunk ,) = next ( stream_iterator ) q.

get_out_stream_info ( 0 )) print ( 'Streaming.' ) print () stream_iterator = streamer. get_src_stream_info ( 0 )) print ( streamer. add_basic_audio_stream ( frames_per_chunk = segment_length, sample_rate = sample_rate ) print ( streamer. NUM_ITER = 100 def stream ( q, format, src, segment_length, sample_rate ): from torchaudio.io import StreamReader print ( 'Building StreamReader.' ) streamer = StreamReader ( src, format = format ) streamer. # This eliminates the need of process synchronization and makes this # tutorial simple. Import torch import torchaudio # The data acquisition process will stop after this number of steps.

Ffmpeg tutorial c++