Update app.py

app.py

@@ -1,50 +1,50 @@
-from os import getenv
-from huggingface_hub import hf_hub_download
-from json import load as json_load , dump as json_dump
-from torch import device as Device
-from torch.cuda import is_available as cuda_is_available
-from TTS.utils.synthesizer import Synthesizer
-
-lang_conf = {
-    "as": "Assamese - অসমীয়া",
-    "bn": "Bangla - বাংলা",
-    "brx": "Boro - बड़ो",
-    "en": "English (Indian accent)",
-    "en+hi": "English+Hindi (Hinglish code-mixed)",
-    "gu": "Gujarati - ગુજરાતી",
-    "hi": "Hindi - हिंदी",
-    "kn": "Kannada - ಕನ್ನಡ",
-    "ml": "Malayalam - മലയാളം",
-    "mni": "Manipuri - মিতৈলোন",
-    "mr": "Marathi - मराठी",
-    "or": "Oriya - ଓଡ଼ିଆ",
-    "pa": "Panjabi - ਪੰਜਾਬੀ",
-    "raj": "Rajasthani - राजस्थानी",
-    "ta": "Tamil - தமிழ்",
-    "te": "Telugu - తెలుగు"
-}
-
-
-class Indic_TTS:
-    def __init__(self,lang,device):
-        model_id = "shethjenil/INDIC_TTS"
-        model_path = hf_hub_download(model_id, lang+"_fastpitch_best_model.pth")
-        vocoder_path = hf_hub_download(model_id, lang+"_hifigan_best_model.pth")
-        vocoder_config_path = hf_hub_download(model_id, lang+"_hifigan_config.json")
-        config_path = hf_hub_download(model_id, lang+"_fastpitch_config.json")
-        speaker_path = hf_hub_download(model_id, lang+"_fastpitch_speakers.pth")
-        conf = json_load(open(config_path))
-        conf['speakers_file'] = conf['model_args']['speakers_file'] = speaker_path
-        json_dump(conf, open(config_path, 'w'))
-        self.synthesizer = Synthesizer(model_path,config_path,vocoder_checkpoint=vocoder_path,vocoder_config=vocoder_config_path,use_cuda=device.type == "cuda")
-        self.speakers = self.synthesizer.tts_model.speaker_manager.speaker_names
-    def text2speech(self,text:str,speaker:str):
-        self.synthesizer.save_wav(self.synthesizer.tts(text,speaker),"output.wav")
-        "output.wav"
-
-indic_tts_lang = getenv("indic_tts_lang")
-tts_lang_name = lang_conf[indic_tts_lang]
-tts_model = Indic_TTS(indic_tts_lang,Device("cuda" if cuda_is_available() else "cpu"))
-
-import gradio as gr
-gr.Interface(tts_model.text2speech,[gr.Textbox(label="Enter Text"),gr.Dropdown(tts_model.speakers, label="speaker"),],gr.Audio(type="filepath", label="Speech"),title=f"{tts_lang_name} TTS").launch()
+from os import getenv
+from huggingface_hub import hf_hub_download
+from json import load as json_load , dump as json_dump
+from torch import device as Device
+from torch.cuda import is_available as cuda_is_available
+from TTS.utils.synthesizer import Synthesizer
+
+lang_conf = {
+    "as": "Assamese - অসমীয়া",
+    "bn": "Bangla - বাংলা",
+    "brx": "Boro - बड़ो",
+    "en": "English (Indian accent)",
+    "en+hi": "English+Hindi (Hinglish code-mixed)",
+    "gu": "Gujarati - ગુજરાતી",
+    "hi": "Hindi - हिंदी",
+    "kn": "Kannada - ಕನ್ನಡ",
+    "ml": "Malayalam - മലയാളം",
+    "mni": "Manipuri - মিতৈলোন",
+    "mr": "Marathi - मराठी",
+    "or": "Oriya - ଓଡ଼ିଆ",
+    "pa": "Panjabi - ਪੰਜਾਬੀ",
+    "raj": "Rajasthani - राजस्थानी",
+    "ta": "Tamil - தமிழ்",
+    "te": "Telugu - తెలుగు"
+}
+
+
+class Indic_TTS:
+    def __init__(self,lang,device):
+        model_id = "shethjenil/INDIC_TTS"
+        model_path = hf_hub_download(model_id, lang+"_fastpitch_best_model.pth")
+        vocoder_path = hf_hub_download(model_id, lang+"_hifigan_best_model.pth")
+        vocoder_config_path = hf_hub_download(model_id, lang+"_hifigan_config.json")
+        config_path = hf_hub_download(model_id, lang+"_fastpitch_config.json")
+        speaker_path = hf_hub_download(model_id, lang+"_fastpitch_speakers.pth")
+        conf = json_load(open(config_path))
+        conf['speakers_file'] = conf['model_args']['speakers_file'] = speaker_path
+        json_dump(conf, open(config_path, 'w'))
+        self.synthesizer = Synthesizer(model_path,config_path,vocoder_checkpoint=vocoder_path,vocoder_config=vocoder_config_path,use_cuda=device.type == "cuda")
+        self.speakers = self.synthesizer.tts_model.speaker_manager.speaker_names
+    def text2speech(self,text:str,speaker:str):
+        self.synthesizer.save_wav(self.synthesizer.tts(text,speaker),"output.wav")
+        return "output.wav"
+
+indic_tts_lang = getenv("indic_tts_lang")
+tts_lang_name = lang_conf[indic_tts_lang]
+tts_model = Indic_TTS(indic_tts_lang,Device("cuda" if cuda_is_available() else "cpu"))
+
+import gradio as gr
+gr.Interface(tts_model.text2speech,[gr.Textbox(label="Enter Text"),gr.Dropdown(tts_model.speakers, label="speaker"),],gr.Audio(type="filepath", label="Speech"),title=f"{tts_lang_name} TTS").launch()