| # MIT License | |
| # | |
| # Copyright (c) 2023 CNRS | |
| # | |
| # Permission is hereby granted, free of charge, to any person obtaining a copy | |
| # of this software and associated documentation files (the "Software"), to deal | |
| # in the Software without restriction, including without limitation the rights | |
| # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| # copies of the Software, and to permit persons to whom the Software is | |
| # furnished to do so, subject to the following conditions: | |
| # | |
| # The above copyright notice and this permission notice shall be included in all | |
| # copies or substantial portions of the Software. | |
| # | |
| # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
| # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
| # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
| # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
| # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
| # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
| # SOFTWARE. | |
| from pyannote.audio import Pipeline, Audio | |
| import torch | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| # initialize pretrained pipeline | |
| self._pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1") | |
| # send pipeline to GPU if available | |
| if torch.cuda.is_available(): | |
| self._pipeline.to(torch.device("cuda")) | |
| # initialize audio reader | |
| self._io = Audio() | |
| def __call__(self, data): | |
| inputs = data.pop("inputs", data) | |
| waveform, sample_rate = self._io(inputs) | |
| parameters = data.pop("parameters", dict()) | |
| diarization = self.pipeline( | |
| {"waveform": waveform, "sample_rate": sample_rate}, **parameters | |
| ) | |
| processed_diarization = [ | |
| { | |
| "speaker": speaker, | |
| "start": f"{turn.start:.3f}", | |
| "end": f"{turn.end:.3f}", | |
| } | |
| for turn, _, speaker in diarization.itertracks(yield_label=True) | |
| ] | |
| return {"diarization": processed_diarization} | |