Metadata-Version: 2.1
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Name: funasr-onnx
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Version: 0.0.3
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Summary: FunASR: A Fundamental End-to-End Speech Recognition Toolkit
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Home-page: https://github.com/alibaba-damo-academy/FunASR.git
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Author: Speech Lab, Alibaba Group, China
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Author-email: funasr@list.alibaba-inc.com
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License: MIT
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Keywords: funasr,asr
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Platform: Any
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Description-Content-Type: text/markdown
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## Using funasr with ONNXRuntime
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### Introduction
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- Model comes from [speech_paraformer](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary).
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### Steps:
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1. Export the model.
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- Command: (`Tips`: torch >= 1.11.0 is required.)
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More details ref to ([export docs](https://github.com/alibaba-damo-academy/FunASR/tree/main/funasr/export))
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- `e.g.`, Export model from modelscope
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```shell
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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 False
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```
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- `e.g.`, Export model from local path, the model'name must be `model.pb`.
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```shell
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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 False
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```
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2. Install the `funasr_onnx`
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install from pip
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```shell
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pip install --upgrade funasr_onnx -i https://pypi.Python.org/simple
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```
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or install from source code
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```shell
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git clone https://github.com/alibaba/FunASR.git && cd FunASR
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cd funasr/runtime/python/funasr_onnx
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python setup.py build
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python setup.py install
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```
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3. Run the demo.
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- Model_dir: the model path, which contains `model.onnx`, `config.yaml`, `am.mvn`.
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- Input: wav formt file, support formats: `str, np.ndarray, List[str]`
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- Output: `List[str]`: recognition result.
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- Example:
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```python
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from funasr_onnx import Paraformer
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model_dir = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
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model = Paraformer(model_dir, batch_size=1)
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wav_path = ['/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
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result = model(wav_path)
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print(result)
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```
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## Performance benchmark
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Please ref to [benchmark](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/python/benchmark_onnx.md)
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## Acknowledge
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1. This project is maintained by [FunASR community](https://github.com/alibaba-damo-academy/FunASR).
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2. We acknowledge [SWHL](https://github.com/RapidAI/RapidASR) for contributing the onnxruntime (for paraformer model).
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