65 lines
1.6 KiB
Python
65 lines
1.6 KiB
Python
import json
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from io import BytesIO
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from pathlib import Path
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from fastapi import APIRouter, Response, UploadFile, Body, responses, Form, Query
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from fastapi.responses import JSONResponse
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from pydantic import BaseModel
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from scipy.io import wavfile
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from base64 import b64encode
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from rvc.modules.vc.modules import VC
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router = APIRouter()
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@router.post("/inference")
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def inference(
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modelpath: Path | UploadFile,
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input_audio: Path | UploadFile,
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res_type: str = Query("blob", enum=["blob", "json"]),
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sid: int = 0,
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f0_up_key: int = 0,
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f0_method: str = Query(
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"rmvpe", enum=["pm", "harvest", "dio", "rmvpe", "rmvpe_gpu"]
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),
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f0_file: Path | None = None,
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index_file: Path | None = None,
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index_rate: float = 0.75,
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filter_radius: int = 3,
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resample_sr: int = 0,
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rms_mix_rate: float = 0.25,
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protect: float = 0.33,
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):
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print(res_type)
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vc = VC()
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vc.get_vc(modelpath)
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tgt_sr, audio_opt, times, _ = vc.vc_inference(
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sid,
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input_audio,
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f0_up_key,
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f0_method,
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f0_file,
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index_file,
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index_rate,
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filter_radius,
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resample_sr,
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rms_mix_rate,
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protect,
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)
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wavfile.write(wv := BytesIO(), tgt_sr, audio_opt)
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print(times)
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if res_type == "blob":
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return responses.StreamingResponse(
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wv,
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media_type="audio/wav",
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headers={"Content-Disposition": "attachment; filename=inference.wav"},
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)
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else:
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return JSONResponse(
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{
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"time": json.loads(json.dumps(times)),
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"audio": b64encode(wv.read()).decode("utf-8"),
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}
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)
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