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Configuration error
Configuration error
Kangarroar
commited on
Commit
•
33de63c
1
Parent(s):
9dc665b
Update app.py
Browse files
app.py
CHANGED
@@ -1,6 +1,43 @@
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import gradio as gr
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model_path = get_model_path()
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demo = gr.Blocks()
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with demo:
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gr.Markdown("# **<p align='center'>DIFF-SVC Inference</p>**")
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@@ -12,11 +49,12 @@ with demo:
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</p>
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"""
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)
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gr.File(label= 'Load your CKPT')
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gr.File(label= 'Load your Config File')
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audio_file = gr.Audio(label = 'Load your WAV', type="filepath")
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gr.Slider(2, 20, value=4)
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b1 = gr.Button("Render")
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import gradio as gr
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from utils.hparams import hparams
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from preprocessing.data_gen_utils import get_pitch_parselmouth,get_pitch_crepe
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import numpy as np
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import matplotlib.pyplot as plt
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import IPython.display as ipd
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import utils
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import librosa
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import torchcrepe
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from infer import *
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import logging
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from infer_tools.infer_tool import *
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import io
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def render_audio(audio_file):
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print(audio_file)
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############
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logging.getLogger('numba').setLevel(logging.WARNING)
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# 工程文件夹名,训练时用的那个
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project_name = "Unnamed"
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model_path = f'./checkpoints/Unnamed/model_ckpt_steps_192000.ckpt'
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config_path=f'./checkpoints/Unnamed/config.yaml'
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hubert_gpu=False
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svc_model = Svc(project_name,config_path,hubert_gpu, model_path)
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print('model loaded')
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wav_fn = audio_file
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demoaudio, sr = librosa.load(wav_fn)
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key = -8 # 音高调整,支持正负(半音)
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# 加速倍数
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pndm_speedup = 20
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wav_gen='queeeeee.wav'#直接改后缀可以保存不同格式音频,如flac可无损压缩
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f0_tst, f0_pred, audio = run_clip(svc_model,file_path=wav_fn, key=key, acc=pndm_speedup, use_crepe=True, use_pe=True, thre=0.05,
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use_gt_mel=False, add_noise_step=500,project_name=project_name,out_path=wav_gen)
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def segment(audio):
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pass # Implement your image segmentation model here...
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demo = gr.Blocks()
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with demo:
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gr.Markdown("# **<p align='center'>DIFF-SVC Inference</p>**")
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</p>
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"""
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)
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ckpt_file = gr.File(label= 'Load your CKPT', type="file")
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config_file = gr.File(label= 'Load your Config File', type="file")
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audio_file = gr.Audio(label = 'Load your WAV', type="filepath")
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gr.Slider(2, 20, value=4)
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b1 = gr.Button("Render")
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b1.click(fn=render_audio, inputs=audio_file)
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demo.launch()
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