From 66022593c8ab92ba5f905c25478c1d0c96b7ba06 Mon Sep 17 00:00:00 2001
From: 雾聪 <wucong.lyb@alibaba-inc.com>
Date: 星期四, 01 二月 2024 16:17:24 +0800
Subject: [PATCH] update run_server.sh & docs
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+([绠�浣撲腑鏂嘳(./quick_start_zh.md)|English)
+
+# Quick Start
+
+You can use FunASR in the following ways:
+
+- Service Deployment SDK
+- Industrial model egs
+- Academic model egs
+
+## Service Deployment SDK
+
+### Python version Example
+Supports real-time streaming speech recognition, uses non-streaming models for error correction, and outputs text with punctuation. Currently, only single client is supported. For multi-concurrency, please refer to the C++ version service deployment SDK below.
+
+#### Server Deployment
+
+```shell
+cd runtime/python/websocket
+python funasr_wss_server.py --port 10095
+```
+
+#### Client Testing
+
+```shell
+python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "5,10,5"
+```
+
+For more examples, please refer to [docs](../runtime/python/websocket/README.md).
+
+### Service Deployment Software
+
+Both high-precision, high-efficiency, and high-concurrency file transcription, as well as low-latency real-time speech recognition, are supported. It also supports Docker deployment and multiple concurrent requests.
+
+##### Docker Installation (optional)
+###### If you have already installed Docker, skip this step.
+
+```shell
+curl -O https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/shell/install_docker.sh;
+sudo bash install_docker.sh
+```
+
+##### Real-time Speech Recognition Service Deployment
+
+###### Docker Image Download and Launch
+Use the following command to pull and launch the FunASR software package Docker image锛圼Get the latest image version](https://github.com/alibaba-damo-academy/FunASR/blob/main/runtime/docs/SDK_advanced_guide_online.md)锛夛細
+
+```shell
+sudo docker pull \
+ registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-online-cpu-0.1.6
+mkdir -p ./funasr-runtime-resources/models
+sudo docker run -p 10096:10095 -it --privileged=true \
+ -v $PWD/funasr-runtime-resources/models:/workspace/models \
+ registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-online-cpu-0.1.6
+```
+
+###### Server Start
+
+After Docker is started, start the funasr-wss-server-2pass service program:
+
+```shell
+cd FunASR/runtime
+nohup bash run_server_2pass.sh \
+ --download-model-dir /workspace/models \
+ --vad-dir damo/speech_fsmn_vad_zh-cn-16k-common-onnx \
+ --model-dir damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx \
+ --online-model-dir damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online-onnx \
+ --punc-dir damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727-onnx \
+ --itn-dir thuduj12/fst_itn_zh \
+ --hotword /workspace/models/hotwords.txt > log.txt 2>&1 &
+
+# If you want to disable SSL, add the parameter: --certfile 0
+# If you want to deploy with a timestamp or nn hotword model, please set --model-dir to the corresponding model:
+# damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-onnx (timestamp)
+# damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404-onnx (nn hotword)
+# If you want to load hotwords on the server side, please configure the hotwords in the host file ./funasr-runtime-resources/models/hotwords.txt (docker mapping address is /workspace/models/hotwords.txt):
+# One hotword per line, format (hotword weight): Alibaba 20
+```
+
+###### Client Testing
+Testing [samples](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/sample/funasr_samples.tar.gz)
+
+```shell
+python3 funasr_wss_client.py --host "127.0.0.1" --port 10096 --mode 2pass
+```
+For more examples, please refer to [docs](https://github.com/alibaba-damo-academy/FunASR/blob/main/runtime/docs/SDK_advanced_guide_online.md)
+
+
+#### File Transcription Service, Mandarin (CPU)
+
+###### Docker Image Download and Launch
+Use the following command to pull and launch the FunASR software package Docker image锛圼Get the latest image version](https://github.com/alibaba-damo-academy/FunASR/blob/main/runtime/docs/SDK_advanced_guide_offline.md)锛夛細
+
+```shell
+sudo docker pull \
+ registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-cpu-0.4.1
+mkdir -p ./funasr-runtime-resources/models
+sudo docker run -p 10095:10095 -it --privileged=true \
+ -v $PWD/funasr-runtime-resources/models:/workspace/models \
+ registry.cn-hangzhou.aliyuncs.com/funasr_repo/funasr:funasr-runtime-sdk-cpu-0.4.1
+```
+
+###### Server Start
+
+After Docker is started, start the funasr-wss-server service program:
+
+```shell
+cd FunASR/runtime
+nohup bash run_server.sh \
+ --download-model-dir /workspace/models \
+ --vad-dir damo/speech_fsmn_vad_zh-cn-16k-common-onnx \
+ --model-dir damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx \
+ --punc-dir damo/punc_ct-transformer_cn-en-common-vocab471067-large-onnx \
+ --lm-dir damo/speech_ngram_lm_zh-cn-ai-wesp-fst \
+ --itn-dir thuduj12/fst_itn_zh \
+ --hotword /workspace/models/hotwords.txt > log.txt 2>&1 &
+
+# If you want to disable SSL, add the parameter: --certfile 0
+# If you want to use timestamp or nn hotword models for deployment, please set --model-dir to the corresponding model:
+# damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-onnx (timestamp)
+# damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404-onnx (nn hotword)
+# If you want to load hotwords on the server side, please configure the hotwords in the host machine file ./funasr-runtime-resources/models/hotwords.txt (docker mapping address is /workspace/models/hotwords.txt):
+# One hotword per line, format (hotword weight): Alibaba 20
+```
+
+##### Client Testing
+
+Testing [samples](https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/sample/funasr_samples.tar.gz)
+```shell
+python3 funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode offline --audio_in "../audio/asr_example.wav"
+```
+
+For more examples, please refer to [docs](https://github.com/alibaba-damo-academy/FunASR/blob/main/runtime/docs/SDK_advanced_guide_offline.md)
+
+
+## Industrial Model Egs
+
+If you want to use the pre-trained industrial models in ModelScope for inference or fine-tuning training, you can refer to the following command:
+
+```python
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+inference_pipeline = pipeline(
+ task=Tasks.auto_speech_recognition,
+ model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
+)
+
+rec_result = inference_pipeline(audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
+print(rec_result)
+# {'text': '娆㈣繋澶у鏉ヤ綋楠岃揪鎽╅櫌鎺ㄥ嚭鐨勮闊宠瘑鍒ā鍨�'}
+```
+
+More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
+
+## Academic model egs
+
+If you want to train from scratch, usually for academic models, you can start training and inference with the following command:
+
+```shell
+cd egs/aishell/paraformer
+. ./run.sh --CUDA_VISIBLE_DEVICES="0,1" --gpu_num=2
+```
+More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
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