from modelscope.pipelines import pipeline
|
from modelscope.utils.constant import Tasks
|
import numpy as np
|
import os
|
|
|
def test_wav_cpu_infer():
|
output_dir = "./outputs"
|
data_path_and_name_and_type = [
|
"data/unit_test/test_wav.scp,speech,sound",
|
"data/unit_test/test_profile.scp,profile,kaldi_ark",
|
]
|
diar_pipeline = pipeline(
|
task=Tasks.speaker_diarization,
|
model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
|
mode="sond",
|
output_dir=output_dir,
|
num_workers=0,
|
log_level="WARNING",
|
)
|
results = diar_pipeline(data_path_and_name_and_type)
|
print(results)
|
|
|
def test_wav_gpu_infer():
|
output_dir = "./outputs"
|
data_path_and_name_and_type = [
|
"data/unit_test/test_wav.scp,speech,sound",
|
"data/unit_test/test_profile.scp,profile,kaldi_ark",
|
]
|
diar_pipeline = pipeline(
|
task=Tasks.speaker_diarization,
|
model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
|
mode="sond",
|
output_dir=output_dir,
|
num_workers=0,
|
log_level="WARNING",
|
)
|
results = diar_pipeline(data_path_and_name_and_type)
|
print(results)
|
|
|
def test_without_profile_gpu_infer():
|
raw_inputs = [
|
"data/unit_test/raw_inputs/record.wav",
|
"data/unit_test/raw_inputs/spk1.wav",
|
"data/unit_test/raw_inputs/spk2.wav",
|
"data/unit_test/raw_inputs/spk3.wav",
|
"data/unit_test/raw_inputs/spk4.wav"
|
]
|
diar_pipeline = pipeline(
|
task=Tasks.speaker_diarization,
|
model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
|
mode="sond_demo",
|
num_workers=0,
|
log_level="WARNING",
|
param_dict={},
|
)
|
results = diar_pipeline(raw_inputs=raw_inputs)
|
print(results)
|
|
|
if __name__ == '__main__':
|
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
|
test_wav_cpu_infer()
|
test_wav_gpu_infer()
|
test_without_profile_gpu_infer()
|
