modify

app.py

@@ -1,21 +1,19 @@
-import gradio as gr
 import base64
 import torch
 import io
+import tempfile
 import scipy.io.wavfile as wavfile
-from PIL import Image
-import numpy as np
-
 import commons
 import utils
+
+import gradio as gr
+import numpy as np
+
+from PIL import Image
 from models import SynthesizerTrn
 from text.symbols import symbols
 from text import text_to_sequence
 
-import subprocess
-import os
-import tempfile
-
 def get_text(text, hps):
     text_norm = text_to_sequence(text, hps.data.text_cleaners)
     if hps.data.add_blank:
@@ -49,13 +47,7 @@ net_g = SynthesizerTrn(
     hps.train.segment_size // hps.data.hop_length,
     **hps.model)
 _ = net_g.eval()
-
-if os.path.isfile(pretrained_model):
-    _ = utils.load_checkpoint(pretrained_model, net_g, None)
-else:
-    # Run the shell script
-    subprocess.call('./startup.sh', shell=True)
-    _ = utils.load_checkpoint(pretrained_model, net_g, None)
+_ = utils.load_checkpoint(pretrained_model, net_g, None)
 
 # Define the function that will be used to generate speech from text
 def generate_speech(text):