app.py

app.py

@@ -0,0 +1,95 @@
+import tempfile
+from typing import Optional
+from TTS.config import load_config
+import gradio as gr
+import numpy as np
+from TTS.utils.manage import ModelManager
+from TTS.utils.synthesizer import Synthesizer
+
+
+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
+
+# 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
+    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,
+    )
+    # synthesize
+    if synthesizer is None:
+        raise NameError("model not found")
+    wavs = synthesizer.tts(text, None)
+    # return output
+    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
+        synthesizer.save_wav(wavs, fp)
+        return fp.name
+
+with gr.Blocks(analytics_enabled=False) as demo:
+    gr.Markdown("<h2 align='center'>🐸💬 CoquiTTS Model Testing Playground 🐸💬</h2>")
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Input Text",
+                value="This sentence has been generated by a speech synthesis system.",
+            )
+            model_select = gr.Dropdown(
+                label="Pick Model: tts_models/<language>/<dataset>/<model_name>",
+                choices=MODEL_NAMES,
+                value="tts_models/en/jenny/jenny"
+            )
+            tts_button = gr.Button("Send", elem_id="send-btn", visible=True)
+
+        with gr.Column():
+            output_audio = gr.Audio(label="Output", type="filepath")
+
+    tts_button.click(
+        tts,
+        inputs=[
+            input_text,
+            model_select,
+        ],
+        outputs=[output_audio],
+    )
+
+# iface = gr.Interface(fn=tts, 
+#                      inputs=[
+#                          gr.Text(label="text", value="Hello, how are you?"),
+#                          gr.Dropdown(choices=MODEL_NAMES, label="Models", info="Chose a model.", default="tts_models/en/jenny/jenny")
+#                          ], 
+#                      outputs=[gr.Audio(label="Output", type="filepath")],
+#                      examples=[
+#                          ["Hello Jhon. Welcome to our group.", "model1.wav"],
+#                          ["Hello Jhon. Welcome to our group.", "model2.mp3"]]
+#                      )
+# iface.launch(share=True, debug=True)
+demo.queue(concurrency_count=16).launch(debug=True)