nevreal commited on
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2ee664d
1 Parent(s): e0821c8

Update app.py

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  1. app.py +1 -218
app.py CHANGED
@@ -1,222 +1,5 @@
1
- import asyncio
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- import datetime
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- import logging
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- import os
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- import time
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- import traceback
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-
8
- import edge_tts
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  import gradio as gr
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- import librosa
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- import torch
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- from fairseq import checkpoint_utils
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- from huggingface_hub import snapshot_download
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-
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-
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- from config import Config
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- from lib.infer_pack.models import (
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- SynthesizerTrnMs256NSFsid,
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- SynthesizerTrnMs256NSFsid_nono,
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- SynthesizerTrnMs768NSFsid,
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- SynthesizerTrnMs768NSFsid_nono,
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- )
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- from rmvpe import RMVPE
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- from vc_infer_pipeline import VC
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-
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- logging.getLogger("fairseq").setLevel(logging.WARNING)
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- logging.getLogger("numba").setLevel(logging.WARNING)
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- logging.getLogger("markdown_it").setLevel(logging.WARNING)
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- logging.getLogger("urllib3").setLevel(logging.WARNING)
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- logging.getLogger("matplotlib").setLevel(logging.WARNING)
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-
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- limitation = os.getenv("SYSTEM") == "spaces"
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-
34
- config = Config()
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-
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- # Edge TTS
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- edge_output_filename = "edge_output.mp3"
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- tts_voice_list = asyncio.get_event_loop().run_until_complete(edge_tts.list_voices())
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- tts_voices = [f"{v['ShortName']}-{v['Gender']}" for v in tts_voice_list]
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-
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- # RVC models
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- model_root = snapshot_download(repo_id="NoCrypt/miku_RVC", token=os.environ["TOKEN"])
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- models = [d for d in os.listdir(model_root) if os.path.isdir(f"{model_root}/{d}")]
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- models.sort()
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-
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-
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- def model_data(model_name):
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- # global n_spk, tgt_sr, net_g, vc, cpt, version, index_file
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- pth_path = [
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- f"{model_root}/{model_name}/{f}"
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- for f in os.listdir(f"{model_root}/{model_name}")
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- if f.endswith(".pth")
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- ][0]
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- print(f"Loading {pth_path}")
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- cpt = torch.load(pth_path, map_location="cpu")
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- tgt_sr = cpt["config"][-1]
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- cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk
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- if_f0 = cpt.get("f0", 1)
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- version = cpt.get("version", "v1")
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- if version == "v1":
61
- if if_f0 == 1:
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- net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
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- else:
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- net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
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- elif version == "v2":
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- if if_f0 == 1:
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- net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
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- else:
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- net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
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- else:
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- raise ValueError("Unknown version")
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- del net_g.enc_q
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- net_g.load_state_dict(cpt["weight"], strict=False)
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- print("Model loaded")
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- net_g.eval().to(config.device)
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- if config.is_half:
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- net_g = net_g.half()
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- else:
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- net_g = net_g.float()
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- vc = VC(tgt_sr, config)
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- # n_spk = cpt["config"][-3]
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-
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- index_files = [
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- f"{model_root}/{model_name}/{f}"
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- for f in os.listdir(f"{model_root}/{model_name}")
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- if f.endswith(".index")
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- ]
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- if len(index_files) == 0:
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- print("No index file found")
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- index_file = ""
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- else:
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- index_file = index_files[0]
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- print(f"Index file found: {index_file}")
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-
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- return tgt_sr, net_g, vc, version, index_file, if_f0
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-
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-
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- def load_hubert():
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- # global hubert_model
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- models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
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- ["hubert_base.pt"],
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- suffix="",
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- )
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- hubert_model = models[0]
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- hubert_model = hubert_model.to(config.device)
106
- if config.is_half:
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- hubert_model = hubert_model.half()
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- else:
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- hubert_model = hubert_model.float()
110
- return hubert_model.eval()
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-
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-
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- def tts(
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- model_name,
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- speed,
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- tts_text,
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- tts_voice,
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- f0_up_key,
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- f0_method,
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- index_rate,
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- protect,
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- filter_radius=3,
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- resample_sr=0,
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- rms_mix_rate=0.25,
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- ):
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- print("------------------")
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- print(datetime.datetime.now())
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- print("tts_text:")
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- print(tts_text)
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- print(f"tts_voice: {tts_voice}, speed: {speed}")
131
- print(f"Model name: {model_name}")
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- print(f"F0: {f0_method}, Key: {f0_up_key}, Index: {index_rate}, Protect: {protect}")
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- try:
134
- if limitation and len(tts_text) > 1000:
135
- print("Error: Text too long")
136
- return (
137
- f"Text characters should be at most 1000 in this huggingface space, but got {len(tts_text)} characters.",
138
- None,
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- None,
140
- )
141
- t0 = time.time()
142
- if speed >= 0:
143
- speed_str = f"+{speed}%"
144
- else:
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- speed_str = f"{speed}%"
146
- asyncio.run(
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- edge_tts.Communicate(
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- tts_text, "-".join(tts_voice.split("-")[:-1]), rate=speed_str
149
- ).save(edge_output_filename)
150
- )
151
- t1 = time.time()
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- edge_time = t1 - t0
153
- audio, sr = librosa.load(edge_output_filename, sr=16000, mono=True)
154
- duration = len(audio) / sr
155
- print(f"Audio duration: {duration}s")
156
- if limitation and duration >= 200:
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- print("Error: Audio too long")
158
- return (
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- f"Audio should be less than 200 seconds in this huggingface space, but got {duration}s.",
160
- edge_output_filename,
161
- None,
162
- )
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- f0_up_key = int(f0_up_key)
164
-
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- tgt_sr, net_g, vc, version, index_file, if_f0 = model_data(model_name)
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- if f0_method == "rmvpe":
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- vc.model_rmvpe = rmvpe_model
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- times = [0, 0, 0]
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- audio_opt = vc.pipeline(
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- hubert_model,
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- net_g,
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- 0,
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- audio,
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- edge_output_filename,
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- times,
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- f0_up_key,
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- f0_method,
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- index_file,
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- # file_big_npy,
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- index_rate,
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- if_f0,
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- filter_radius,
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- tgt_sr,
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- resample_sr,
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- rms_mix_rate,
186
- version,
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- protect,
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- None,
189
- )
190
- if tgt_sr != resample_sr >= 16000:
191
- tgt_sr = resample_sr
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- info = f"Success. Time: edge-tts: {edge_time}s, npy: {times[0]}s, f0: {times[1]}s, infer: {times[2]}s"
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- print(info)
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- return (
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- info,
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- edge_output_filename,
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- (tgt_sr, audio_opt),
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- )
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- except EOFError:
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- info = (
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- "It seems that the edge-tts output is not valid. "
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- "This may occur when the input text and the speaker do not match. "
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- "For example, maybe you entered Japanese (without alphabets) text but chose non-Japanese speaker?"
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- )
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- print(info)
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- return info, None, None
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- except:
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- info = traceback.format_exc()
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- print(info)
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- return info, None, None
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-
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-
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- print("Loading hubert model...")
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- hubert_model = load_hubert()
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- print("Hubert model loaded.")
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-
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- print("Loading rmvpe model...")
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- rmvpe_model = RMVPE("rmvpe.pt", config.is_half, config.device)
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- print("rmvpe model loaded.")
220
 
221
  initial_md = """
222
  ![banner that says mikutts](https://huggingface.co/spaces/NoCrypt/mikuTTS/resolve/main/imgs/banner_mikutts.webp)
 
 
 
 
 
 
 
 
 
1
  import gradio as gr
2
+ import rvc *
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
 
4
  initial_md = """
5
  ![banner that says mikutts](https://huggingface.co/spaces/NoCrypt/mikuTTS/resolve/main/imgs/banner_mikutts.webp)