Cambio app.py

app.py

@@ -5,50 +5,42 @@ import gradio as gr
 import numpy as np
 from TTS.utils.manage import ModelManager
 from TTS.utils.synthesizer import Synthesizer
+import os
 
 
-MODELS = {}
-SPEAKERS = {}
-MAX_TXT_LEN = 100
-
-
-manager = ModelManager()
-MODEL_NAMES = manager.list_tts_models()
-
-# filter out multi-speaker models and slow wavegrad vocoders
-filters = ["vctk", "your_tts", "ek1"]
-MODEL_NAMES = [model_name for model_name in MODEL_NAMES if not any(f in model_name for f in filters)]
-
-EN = [el for el in MODEL_NAMES if "/en/" in el]
-OTHER = [el for el in MODEL_NAMES if "/en/" not in el]
-EN[0], EN[5] = EN[5], EN[0]
-MODEL_NAMES = EN + OTHER
+MODEL_NAMES = ["Celtia", "Icia", "Sabela"]
 
 # reorder models
 print(MODEL_NAMES)
 
 
-def tts(text: str, model_name: str):
-    if len(text) > MAX_TXT_LEN:
-        text = text[:MAX_TXT_LEN]
-        print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.")
-    print(text, model_name)
-    # download model
-    model_path, config_path, model_item = manager.download_model(model_name)
-    vocoder_name: Optional[str] = model_item["default_vocoder"]
-    # download vocoder
+def tts(text: str,
+        model_file: str = "icia.pth"
+):
+
+    model_path = os.path.join(os.getcwd(), model_file)
+    # if text is "celtia" take celtia.pth and celtia_config.json
+    if text == "Celtia":
+        config_path = "celtia_config.json"
+        model_file = "celtia.pth"
+    elif text == "Icia":
+        config_path = "icia_config.json"
+        model_file = "icia.pth"
+    else:
+        config_path = "sabela_config.json"
+        model_file = "sabela.pth"
+
     vocoder_path = None
     vocoder_config_path = None
-    if vocoder_name is not None:
-        vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name)
-    # init synthesizer
+
     synthesizer = Synthesizer(
-        model_path, config_path, None, None, vocoder_path, vocoder_config_path,
+        model_path, config_path, None, vocoder_path, vocoder_config_path,
     )
+
     # synthesize
     if synthesizer is None:
         raise NameError("model not found")
-    wavs = synthesizer.tts(text, None)
+    wavs = synthesizer.tts(text)
     # return output
     with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
         synthesizer.save_wav(wavs, fp)