44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
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import argparse
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import base64
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import io
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import soundfile as sf
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import uvicorn
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from fastapi import FastAPI, Body
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app = FastAPI()
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from funasr_onnx import Paraformer
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model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-onnx"
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model = Paraformer(model_dir, batch_size=1, quantize=True)
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async def recognition_onnx(waveform):
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result = model(waveform)[0]["preds"][0]
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return result
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@app.post("/api/asr")
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async def asr(item: dict = Body(...)):
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try:
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audio_bytes = base64.b64decode(bytes(item["wav_base64"], "utf-8"))
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waveform, _ = sf.read(io.BytesIO(audio_bytes))
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result = await recognition_onnx(waveform)
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ret = {"results": result, "code": 0}
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except:
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print("请求出错，这里是处理出错的")
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ret = {"results": "", "code": 1}
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return ret
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="API Service")
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parser.add_argument("--listen", default="0.0.0.0", type=str, help="the network to listen")
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parser.add_argument("--port", default=8888, type=int, help="the port to listen")
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args = parser.parse_args()
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print("start...")
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print("server on:", args)
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uvicorn.run(app, host=args.listen, port=args.port)
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