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语帆 2024-02-23 16:56:02 +08:00
parent d60306e7a4
commit 6a8c943435
2 changed files with 11 additions and 6 deletions
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1
funasr/models/lcbnet/model.py
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@ -425,6 +425,7 @@ class LCBNet(nn.Module):
else: else:
# extract fbank feats # extract fbank feats
time1 = time.perf_counter() time1 = time.perf_counter()
pdb.set_trace()
audio_sample_list = load_audio_text_image_video(data_in, fs=frontend.fs, audio_fs=kwargs.get("fs", 16000), audio_sample_list = load_audio_text_image_video(data_in, fs=frontend.fs, audio_fs=kwargs.get("fs", 16000),
data_type=kwargs.get("data_type", "sound"), data_type=kwargs.get("data_type", "sound"),
tokenizer=tokenizer) tokenizer=tokenizer)

16
funasr/utils/load_utils.py
View File

@ -13,30 +13,34 @@ try:
from funasr.download.file import download_from_url from funasr.download.file import download_from_url
except: except:
print("urllib is not installed, if you infer from url, please install it first.") print("urllib is not installed, if you infer from url, please install it first.")
import pdb
def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs: int = 16000, data_type="sound", tokenizer=None, **kwargs): def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs: int = 16000, data_type="sound", tokenizer=None, **kwargs):
pdb.set_trace()
if isinstance(data_or_path_or_list, (list, tuple)): if isinstance(data_or_path_or_list, (list, tuple)):
if data_type is not None and isinstance(data_type, (list, tuple)): if data_type is not None and isinstance(data_type, (list, tuple)):
pdb.set_trace()
data_types = [data_type] * len(data_or_path_or_list) data_types = [data_type] * len(data_or_path_or_list)
data_or_path_or_list_ret = [[] for d in data_type] data_or_path_or_list_ret = [[] for d in data_type]
pdb.set_trace()
for i, (data_type_i, data_or_path_or_list_i) in enumerate(zip(data_types, data_or_path_or_list)): for i, (data_type_i, data_or_path_or_list_i) in enumerate(zip(data_types, data_or_path_or_list)):
for j, (data_type_j, data_or_path_or_list_j) in enumerate(zip(data_type_i, data_or_path_or_list_i)): for j, (data_type_j, data_or_path_or_list_j) in enumerate(zip(data_type_i, data_or_path_or_list_i)):
pdb.set_trace()
data_or_path_or_list_j = load_audio_text_image_video(data_or_path_or_list_j, fs=fs, audio_fs=audio_fs, data_type=data_type_j, tokenizer=tokenizer, **kwargs) data_or_path_or_list_j = load_audio_text_image_video(data_or_path_or_list_j, fs=fs, audio_fs=audio_fs, data_type=data_type_j, tokenizer=tokenizer, **kwargs)
pdb.set_trace()
data_or_path_or_list_ret[j].append(data_or_path_or_list_j) data_or_path_or_list_ret[j].append(data_or_path_or_list_j)
return data_or_path_or_list_ret return data_or_path_or_list_ret
else: else:
return [load_audio_text_image_video(audio, fs=fs, audio_fs=audio_fs, data_type=data_type, **kwargs) for audio in data_or_path_or_list] return [load_audio_text_image_video(audio, fs=fs, audio_fs=audio_fs, data_type=data_type, **kwargs) for audio in data_or_path_or_list]
pdb.set_trace()
if isinstance(data_or_path_or_list, str) and data_or_path_or_list.startswith('http'): # download url to local file if isinstance(data_or_path_or_list, str) and data_or_path_or_list.startswith('http'): # download url to local file
data_or_path_or_list = download_from_url(data_or_path_or_list) data_or_path_or_list = download_from_url(data_or_path_or_list)
pdb.set_trace()
if isinstance(data_or_path_or_list, str) and os.path.exists(data_or_path_or_list): # local file if isinstance(data_or_path_or_list, str) and os.path.exists(data_or_path_or_list): # local file
pdb.set_trace()
if data_type is None or data_type == "sound": if data_type is None or data_type == "sound":
data_or_path_or_list, audio_fs = torchaudio.load(data_or_path_or_list) data_or_path_or_list, audio_fs = torchaudio.load(data_or_path_or_list)
if kwargs.get("reduce_channels", True): if kwargs.get("reduce_channels", True):
@ -59,7 +63,7 @@ def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs:
else: else:
pass pass
# print(f"unsupport data type: {data_or_path_or_list}, return raw data") # print(f"unsupport data type: {data_or_path_or_list}, return raw data")
pdb.set_trace()
if audio_fs != fs and data_type != "text": if audio_fs != fs and data_type != "text":
resampler = torchaudio.transforms.Resample(audio_fs, fs) resampler = torchaudio.transforms.Resample(audio_fs, fs)
data_or_path_or_list = resampler(data_or_path_or_list[None, :])[0, :] data_or_path_or_list = resampler(data_or_path_or_list[None, :])[0, :]