From 1e66d418b811404854c1c686de76efdda154a61f Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期二, 18 四月 2023 22:56:18 +0800
Subject: [PATCH] docs

---
 funasr/runtime/python/onnxruntime/README.md |  115 +++++++++++++++++++++++++++++++++++++++++++++++++++------
 1 files changed, 103 insertions(+), 12 deletions(-)

diff --git a/funasr/runtime/python/onnxruntime/README.md b/funasr/runtime/python/onnxruntime/README.md
index e85e08a..e52f76b 100644
--- a/funasr/runtime/python/onnxruntime/README.md
+++ b/funasr/runtime/python/onnxruntime/README.md
@@ -35,22 +35,113 @@
 # pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
 ```
 
-## Run the demo
-- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`.
+## Inference with runtime
+### Speech Recognition
+#### Paraformer
+ ```python
+ from funasr_onnx import Paraformer
+
+ model_dir = "./export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
+ model = Paraformer(model_dir, batch_size=1)
+
+ wav_path = ['./export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
+
+ result = model(wav_path)
+ print(result)
+ ```
+- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
 - Input: wav formt file, support formats: `str, np.ndarray, List[str]`
-- Output: `List[str]`: recognition result.
-- Example:
-     ```python
-     from funasr_onnx import Paraformer
+- Output: `List[str]`: recognition result
 
-     model_dir = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
-     model = Paraformer(model_dir, batch_size=1)
+#### Paraformer-online
 
-     wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
+### Voice Activity Detection
+#### FSMN-VAD
+```python
+from funasr_onnx import Fsmn_vad
 
-     result = model(wav_path)
-     print(result)
-     ```
+model_dir = "./export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch"
+wav_path = "./export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/example/vad_example.wav"
+model = Fsmn_vad(model_dir)
+
+result = model(wav_path)
+print(result)
+```
+- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
+- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
+- Output: `List[str]`: recognition result
+
+#### FSMN-VAD-online
+```python
+from funasr_onnx import Fsmn_vad_online
+import soundfile
+
+
+model_dir = "./export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch"
+wav_path = "./export/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/example/vad_example.wav"
+model = Fsmn_vad_online(model_dir)
+
+
+##online vad
+speech, sample_rate = soundfile.read(wav_path)
+speech_length = speech.shape[0]
+#
+sample_offset = 0
+step = 1600
+param_dict = {'in_cache': []}
+for sample_offset in range(0, speech_length, min(step, speech_length - sample_offset)):
+    if sample_offset + step >= speech_length - 1:
+        step = speech_length - sample_offset
+        is_final = True
+    else:
+        is_final = False
+    param_dict['is_final'] = is_final
+    segments_result = model(audio_in=speech[sample_offset: sample_offset + step],
+                            param_dict=param_dict)
+    if segments_result:
+        print(segments_result)
+```
+- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
+- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
+- Output: `List[str]`: recognition result
+
+### Punctuation Restoration
+#### CT-Transformer
+```python
+from funasr_onnx import CT_Transformer
+
+model_dir = "./export/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch"
+model = CT_Transformer(model_dir)
+
+text_in="璺ㄥ娌虫祦鏄吇鑲叉部宀镐汉姘戠殑鐢熷懡涔嬫簮闀挎湡浠ユ潵涓哄府鍔╀笅娓稿湴鍖洪槻鐏惧噺鐏句腑鏂规妧鏈汉鍛樺湪涓婃父鍦板尯鏋佷负鎭跺姡鐨勮嚜鐒舵潯浠朵笅鍏嬫湇宸ㄥぇ鍥伴毦鐢氳嚦鍐掔潃鐢熷懡鍗遍櫓鍚戝嵃鏂规彁渚涙睕鏈熸按鏂囪祫鏂欏鐞嗙揣鎬ヤ簨浠朵腑鏂归噸瑙嗗嵃鏂瑰湪璺ㄥ娌虫祦闂涓婄殑鍏冲垏鎰挎剰杩涗竴姝ュ畬鍠勫弻鏂硅仈鍚堝伐浣滄満鍒跺嚒鏄腑鏂硅兘鍋氱殑鎴戜滑閮戒細鍘诲仛鑰屼笖浼氬仛寰楁洿濂芥垜璇峰嵃搴︽湅鍙嬩滑鏀惧績涓浗鍦ㄤ笂娓哥殑浠讳綍寮�鍙戝埄鐢ㄩ兘浼氱粡杩囩瀛﹁鍒掑拰璁鸿瘉鍏奸【涓婁笅娓哥殑鍒╃泭"
+result = model(text_in)
+print(result[0])
+```
+- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
+- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
+- Output: `List[str]`: recognition result
+
+#### CT-Transformer-online
+```python
+from funasr_onnx import CT_Transformer_VadRealtime
+
+model_dir = "./export/damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727"
+model = CT_Transformer_VadRealtime(model_dir)
+
+text_in  = "璺ㄥ娌虫祦鏄吇鑲叉部宀竱浜烘皯鐨勭敓鍛戒箣婧愰暱鏈熶互鏉ヤ负甯姪涓嬫父鍦板尯闃茬伨鍑忕伨涓柟鎶�鏈汉鍛榺鍦ㄤ笂娓稿湴鍖烘瀬涓烘伓鍔g殑鑷劧鏉′欢涓嬪厠鏈嶅法澶у洶闅剧敋鑷冲啋鐫�鐢熷懡鍗遍櫓|鍚戝嵃鏂规彁渚涙睕鏈熸按鏂囪祫鏂欏鐞嗙揣鎬ヤ簨浠朵腑鏂归噸瑙嗗嵃鏂瑰湪璺ㄥ娌虫祦>闂涓婄殑鍏冲垏|鎰挎剰杩涗竴姝ュ畬鍠勫弻鏂硅仈鍚堝伐浣滄満鍒秥鍑℃槸|涓柟鑳藉仛鐨勬垜浠瑋閮戒細鍘诲仛鑰屼笖浼氬仛寰楁洿濂芥垜璇峰嵃搴︽湅鍙嬩滑鏀惧績涓浗鍦ㄤ笂娓哥殑|浠讳綍寮�鍙戝埄鐢ㄩ兘浼氱粡杩囩瀛瑙勫垝鍜岃璇佸吋椤句笂涓嬫父鐨勫埄鐩�"
+
+vads = text_in.split("|")
+rec_result_all=""
+param_dict = {"cache": []}
+for vad in vads:
+    result = model(vad, param_dict=param_dict)
+    rec_result_all += result[0]
+
+print(rec_result_all)
+```
+- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`
+- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
+- Output: `List[str]`: recognition result
 
 ## Performance benchmark
 

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