From 55c09aeaa25b4bb88a50e09ba68fa6ff00a6d676 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期一, 15 一月 2024 20:10:39 +0800
Subject: [PATCH] update readme, fix seaco bug
---
funasr/utils/load_utils.py | 26 ++++++++++++++++++--------
1 files changed, 18 insertions(+), 8 deletions(-)
diff --git a/funasr/utils/load_utils.py b/funasr/utils/load_utils.py
index 39b708a..4e131a8 100644
--- a/funasr/utils/load_utils.py
+++ b/funasr/utils/load_utils.py
@@ -16,7 +16,7 @@
-def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs: int = 16000, data_type="sound", tokenizer=None):
+def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs: int = 16000, data_type="sound", tokenizer=None, **kwargs):
if isinstance(data_or_path_or_list, (list, tuple)):
if data_type is not None and isinstance(data_type, (list, tuple)):
@@ -26,24 +26,34 @@
for j, (data_type_j, data_or_path_or_list_j) in enumerate(zip(data_type_i, data_or_path_or_list_i)):
- 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)
+ 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_ret[j].append(data_or_path_or_list_j)
return data_or_path_or_list_ret
else:
- return [load_audio_text_image_video(audio, fs=fs, audio_fs=audio_fs, data_type=data_type) for audio in data_or_path_or_list]
- if isinstance(data_or_path_or_list, str) and data_or_path_or_list.startswith('http'):
+ 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]
+
+ 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)
- if isinstance(data_or_path_or_list, str) and os.path.exists(data_or_path_or_list):
+
+ if isinstance(data_or_path_or_list, str) and os.path.exists(data_or_path_or_list): # local file
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 = data_or_path_or_list[0, :]
- # elif data_type == "text" and tokenizer is not None:
- # data_or_path_or_list = tokenizer.encode(data_or_path_or_list)
+ elif data_type == "text" and tokenizer is not None:
+ data_or_path_or_list = tokenizer.encode(data_or_path_or_list)
+ elif data_type == "image": # undo
+ pass
+ elif data_type == "video": # undo
+ pass
+
+ # if data_in is a file or url, set is_final=True
+ if "cache" in kwargs:
+ kwargs["cache"]["is_final"] = True
elif isinstance(data_or_path_or_list, str) and data_type == "text" and tokenizer is not None:
data_or_path_or_list = tokenizer.encode(data_or_path_or_list)
elif isinstance(data_or_path_or_list, np.ndarray): # audio sample point
- data_or_path_or_list = np.squeeze(data_or_path_or_list) # [n_samples,]
+ data_or_path_or_list = torch.from_numpy(data_or_path_or_list).squeeze() # [n_samples,]
else:
pass
# print(f"unsupport data type: {data_or_path_or_list}, return raw data")
--
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