mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
fixbug for sd and sv
This commit is contained in:
parent
0a6ff596c6
commit
267dddcdbb
@ -135,8 +135,10 @@ def inference_launch(mode, **kwargs):
|
||||
"sv_train_config": "sv.yaml",
|
||||
"sv_model_file": "sv.pth",
|
||||
}
|
||||
if "param_dict" in kwargs:
|
||||
kwargs["param_dict"].update(param_dict)
|
||||
if "param_dict" in kwargs and kwargs["param_dict"] is not None:
|
||||
for key in param_dict:
|
||||
if key not in kwargs["param_dict"]:
|
||||
kwargs["param_dict"][key] = param_dict[key]
|
||||
else:
|
||||
kwargs["param_dict"] = param_dict
|
||||
return inference_modelscope(**kwargs)
|
||||
|
||||
@ -33,6 +33,8 @@ from funasr.utils.types import str2triple_str
|
||||
from funasr.utils.types import str_or_none
|
||||
from scipy.ndimage import median_filter
|
||||
from funasr.utils.misc import statistic_model_parameters
|
||||
from funasr.datasets.iterable_dataset import load_bytes
|
||||
|
||||
|
||||
class Speech2Diarization:
|
||||
"""Speech2Xvector class
|
||||
@ -257,6 +259,9 @@ def inference_modelscope(
|
||||
assert "sv_model_file" in param_dict, "sv_model_file must be provided in param_dict."
|
||||
sv_train_config = param_dict["sv_train_config"]
|
||||
sv_model_file = param_dict["sv_model_file"]
|
||||
if "model_dir" in param_dict:
|
||||
sv_train_config = os.path.join(param_dict["model_dir"], sv_train_config)
|
||||
sv_model_file = os.path.join(param_dict["model_dir"], sv_model_file)
|
||||
from funasr.bin.sv_inference import Speech2Xvector
|
||||
speech2xvector_kwargs = dict(
|
||||
sv_train_config=sv_train_config,
|
||||
@ -320,7 +325,9 @@ def inference_modelscope(
|
||||
def prepare_dataset():
|
||||
for idx, example in enumerate(raw_inputs):
|
||||
# read waveform file
|
||||
example = [soundfile.read(x)[0] if isinstance(example[0], str) else x
|
||||
example = [load_bytes(x) if isinstance(x, bytes) else x
|
||||
for x in example]
|
||||
example = [soundfile.read(x)[0] if isinstance(x, str) else x
|
||||
for x in example]
|
||||
# convert torch tensor to numpy array
|
||||
example = [x.numpy() if isinstance(example[0], torch.Tensor) else x
|
||||
|
||||
Loading…
Reference in New Issue
Block a user