Merge branch 'main' of github.com:alibaba-damo-academy/FunASR add

游雁

2023-09-13 33d3d2084403fd34b79c835d2f2fe04f6cd8f738

 funasr/bin/diar_inference_launch.py

@@ -18,7 +18,6 @@
import soundfile
import torch
from scipy.signal import medfilt
from typeguard import check_argument_types

from funasr.bin.diar_infer import Speech2DiarizationSOND, Speech2DiarizationEEND
from funasr.datasets.iterable_dataset import load_bytes
@@ -52,7 +51,6 @@
        mode: str = "sond",
        **kwargs,
):
    assert check_argument_types()
    ncpu = kwargs.get("ncpu", 1)
    torch.set_num_threads(ncpu)
    if batch_size > 1:
@@ -94,10 +92,7 @@
            embedding_node="resnet1_dense"
        )
        logging.info("speech2xvector_kwargs: {}".format(speech2xvector_kwargs))
        speech2xvector = Speech2Xvector.from_pretrained(
            model_tag=model_tag,
            **speech2xvector_kwargs,
        )
        speech2xvector = Speech2Xvector(**speech2xvector_kwargs)
        speech2xvector.sv_model.eval()

    # 2b. Build speech2diar
@@ -111,10 +106,7 @@
        dur_threshold=dur_threshold,
    )
    logging.info("speech2diarization_kwargs: {}".format(speech2diar_kwargs))
    speech2diar = Speech2DiarizationSOND.from_pretrained(
        model_tag=model_tag,
        **speech2diar_kwargs,
    )
    speech2diar = Speech2DiarizationSOND(**speech2diar_kwargs)
    speech2diar.diar_model.eval()

    def output_results_str(results: dict, uttid: str):
@@ -233,7 +225,6 @@
        param_dict: Optional[dict] = None,
        **kwargs,
):
    assert check_argument_types()
    ncpu = kwargs.get("ncpu", 1)
    torch.set_num_threads(ncpu)
    if batch_size > 1:
@@ -260,10 +251,7 @@
        dtype=dtype,
    )
    logging.info("speech2diarization_kwargs: {}".format(speech2diar_kwargs))
    speech2diar = Speech2DiarizationEEND.from_pretrained(
        model_tag=model_tag,
        **speech2diar_kwargs,
    )
    speech2diar = Speech2DiarizationEEND(**speech2diar_kwargs)
    speech2diar.diar_model.eval()

    def output_results_str(results: dict, uttid: str):
@@ -465,11 +453,17 @@
        help="The batch size for inference",
    )
    group.add_argument(
        "--diar_smooth_size",
        "--smooth_size",
        type=int,
        default=121,
        help="The smoothing size for post-processing"
    )
    group.add_argument(
        "--dur_threshold",
        type=int,
        default=10,
        help="The threshold of minimum duration"
    )

    return parser