mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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import numpy as np
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import os
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def test_wav_cpu_infer():
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output_dir = "./outputs"
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data_path_and_name_and_type = [
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"data/unit_test/test_wav.scp,speech,sound",
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"data/unit_test/test_profile.scp,profile,kaldi_ark",
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]
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diar_pipeline = pipeline(
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task=Tasks.speaker_diarization,
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model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
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mode="sond",
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output_dir=output_dir,
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num_workers=0,
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log_level="WARNING",
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)
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results = diar_pipeline(data_path_and_name_and_type)
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print(results)
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def test_wav_gpu_infer():
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output_dir = "./outputs"
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data_path_and_name_and_type = [
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"data/unit_test/test_wav.scp,speech,sound",
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"data/unit_test/test_profile.scp,profile,kaldi_ark",
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]
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diar_pipeline = pipeline(
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task=Tasks.speaker_diarization,
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model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
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mode="sond",
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output_dir=output_dir,
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num_workers=0,
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log_level="WARNING",
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)
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results = diar_pipeline(data_path_and_name_and_type)
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print(results)
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def test_without_profile_gpu_infer():
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raw_inputs = [
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"data/unit_test/raw_inputs/record.wav",
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"data/unit_test/raw_inputs/spk1.wav",
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"data/unit_test/raw_inputs/spk2.wav",
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"data/unit_test/raw_inputs/spk3.wav",
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"data/unit_test/raw_inputs/spk4.wav"
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]
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diar_pipeline = pipeline(
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task=Tasks.speaker_diarization,
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model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
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mode="sond_demo",
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sv_model="damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch",
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sv_model_revision="master",
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num_workers=0,
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log_level="WARNING",
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param_dict={},
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)
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results = diar_pipeline(raw_inputs)
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print(results)
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def test_url_without_profile_gpu_infer():
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raw_inputs = [
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/record.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk1.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk2.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk3.wav",
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"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk4.wav",
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]
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diar_pipeline = pipeline(
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task=Tasks.speaker_diarization,
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model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
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mode="sond_demo",
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sv_model="damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch",
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sv_model_revision="master",
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num_workers=0,
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log_level="WARNING",
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param_dict={},
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)
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results = diar_pipeline(raw_inputs)
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print(results)
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if __name__ == '__main__':
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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test_wav_cpu_infer()
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test_wav_gpu_infer()
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test_without_profile_gpu_infer()
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test_url_without_profile_gpu_infer()
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