From 4f8bce944e273e317cb84c7046ea514b9d958b4b Mon Sep 17 00:00:00 2001
From: zhuzizyf <42790740+zhuzizyf@users.noreply.github.com>
Date: 星期六, 22 四月 2023 14:54:49 +0800
Subject: [PATCH] Update FsmnVad.cc
---
funasr/runtime/python/onnxruntime/README.md | 108 +++++++++++++++++++++++-------------------------------
1 files changed, 46 insertions(+), 62 deletions(-)
diff --git a/funasr/runtime/python/onnxruntime/README.md b/funasr/runtime/python/onnxruntime/README.md
index 99dba99..e85e08a 100644
--- a/funasr/runtime/python/onnxruntime/README.md
+++ b/funasr/runtime/python/onnxruntime/README.md
@@ -1,77 +1,61 @@
-## Using paraformer with ONNXRuntime
+# ONNXRuntime-python
-<p align="left">
- <a href=""><img src="https://img.shields.io/badge/Python->=3.7,<=3.10-aff.svg"></a>
- <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-pink.svg"></a>
-</p>
+## Export the model
+### Install [modelscope and funasr](https://github.com/alibaba-damo-academy/FunASR#installation)
-### Introduction
-- Model comes from [speech_paraformer](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary).
+```shell
+pip3 install torch torchaudio
+pip install -U modelscope
+pip install -U funasr
+```
+
+### Export [onnx model](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export)
+
+```shell
+python -m funasr.export.export_model --model-name damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch --export-dir ./export --type onnx --quantize True
+```
-### Steps:
-1. Export the model.
- - Command: (`Tips`: torch 1.11.0 is required.)
+## Install the `funasr_onnx`
- ```shell
- python -m funasr.export.export_model [model_name] [export_dir] [true]
- ```
- `model_name`: the model is to export.
+install from pip
+```shell
+pip install -U funasr_onnx
+# For the users in China, you could install with the command:
+# pip install -U funasr_onnx -i https://mirror.sjtu.edu.cn/pypi/web/simple
+```
- `export_dir`: the dir where the onnx is export.
+or install from source code
- More details ref to ([export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export))
+```shell
+git clone https://github.com/alibaba/FunASR.git && cd FunASR
+cd funasr/runtime/python/onnxruntime
+pip install -e ./
+# For the users in China, you could install with the command:
+# pip install -e ./ -i https://mirror.sjtu.edu.cn/pypi/web/simple
+```
- - `e.g.`, Export model from modelscope
- ```shell
- python -m funasr.export.export_model 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true
- ```
- - `e.g.`, Export model from local path, the model'name must be `model.pb`.
- ```shell
- python -m funasr.export.export_model '/mnt/workspace/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch' "./export" true
- ```
+## Run the demo
+- 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
+ 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)
-2. Install the `rapid_paraformer`.
- - Build the rapid_paraformer `whl`
- ```shell
- git clone https://github.com/alibaba/FunASR.git && cd FunASR
- cd funasr/runtime/python/onnxruntime/rapid_paraformer
- python setup.py bdist_wheel
- ```
- - Install the build `whl`
- ```bash
- pip install dist/rapid_paraformer-0.0.1-py3-none-any.whl
+ wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
+
+ result = model(wav_path)
+ print(result)
```
-3. Run the demo.
- - 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 rapid_paraformer import Paraformer
+## Performance benchmark
- 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)
-
- wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
-
- result = model(wav_path)
- print(result)
- ```
-
-## Speed
-
-Environment锛欼ntel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz
-
-Test [wav, 5.53s, 100 times avg.](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav)
-
-| Backend | RTF |
-|:-------:|:-----------------:|
-| Pytorch | 0.110 |
-| Onnx | 0.038 |
-
+Please ref to [benchmark](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_onnx.md)
## Acknowledge
-1. We acknowledge [SWHL](https://github.com/RapidAI/RapidASR) for contributing the onnxruntime(python api).
+1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).
+2. We acknowledge [SWHL](https://github.com/RapidAI/RapidASR) for contributing the onnxruntime (for paraformer model).
--
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