Create app.py

app.py

@@ -0,0 +1,51 @@
+import gradio as gr
+from pathlib import Path
+
+from utils.hparams import hparams
+from preprocessing.data_gen_utils import get_pitch_parselmouth, get_pitch_crepe
+import numpy as np
+import matplotlib.pyplot as plt
+import librosa
+import utils
+import touchcrepe
+from infer import *
+import logging
+
+import tempfile
+
+from infer_tools.infer_tool import *
+
+# 모델 가져오기
+project_name = "duckaloid" 
+model_path = "model_ckpt_steps_50000.ckpt"
+config_path="config.yaml"
+hubert_gpu=False
+svc_model = Svc(project_name,config_path,hubert_gpu, model_path)
+
+pndm_speedup = 20
+add_noise_step = 500
+thre = 0.05
+use_crepe = False
+use_pe = False
+use_gt_mel = False
+
+
+def infer(audios, key):
+    #save audios into local storage
+    file_path = Path(tempfile.mkdtemp()) / "input.wav"
+    librosa.output.write_wav(file_path, audios)
+
+    demoaudio, sr = librosa.load("input.wav")
+    # infer
+    f0_tst, f0_pred, audio = run_clip(svc_model,file_path="input.wav", key=key, acc=pndm_speedup, use_crepe=use_crepe, use_pe=use_pe, thre=thre,
+                                            use_gt_mel=use_gt_mel, add_noise_step=add_noise_step,project_name=project_name,out_path="output.wav")
+    
+    # return file
+    return audio
+    
+
+iface = gr.Interface(
+    fn=infer,
+    inputs=[gr.inputs.Audio(source="microphone", type="numpy", label="Audio Input"),gr.Slider(minimum=-12, maximum=12, step=1)],
+    outputs="audio")
+iface.launch()