Add application file

app.py

@@ -0,0 +1,100 @@
+import os
+import torch
+import gradio as gr
+from openvoice import se_extractor
+from openvoice.api import ToneColorConverter
+from transformers import pipeline
+import scipy
+from pathlib import Path
+
+# Output directory setup
+output_dir = './openvoice_outputs'
+os.makedirs(output_dir, exist_ok=True)
+
+# Function to get model names from a directory
+def get_model_names(model_dir):
+    model_paths = Path(model_dir).glob('*')
+    return [model_path.name for model_path in model_paths if model_path.is_dir()]
+
+def generate_speech(text, model_path):
+    synthesiser = pipeline("text-to-speech", model_path, device=0 if torch.cuda.is_available() else -1)
+    speech = synthesiser(text)
+    
+    # Resample to 48kHz if needed
+    if speech["sampling_rate"] != 48000:
+        resampled_audio = scipy.signal.resample(speech["audio"][0], int(len(speech["audio"][0]) * 48000 / speech["sampling_rate"]))
+        sampling_rate = 48000
+    else:
+        resampled_audio = speech["audio"][0]
+        sampling_rate = speech["sampling_rate"]
+    
+    return sampling_rate, resampled_audio
+
+def save_audio(sampling_rate, audio_data, filename="output.wav"):
+    scipy.io.wavfile.write(filename, rate=sampling_rate, data=audio_data)
+    return filename
+
+def voice_cloning(base_speaker, reference_speaker, model_version, device_choice, vad_select):
+    try:
+        # Determine paths and device
+        ckpt_converter = f'./OPENVOICE_MODELS/{model_version}'
+        device = "cuda:0" if device_choice == "GPU" and torch.cuda.is_available() else "cpu"
+        print(f"Device: {device}")
+        
+        # Load the ToneColorConverter
+        tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
+        tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
+
+        # Extract speaker embeddings
+        source_se, _ = se_extractor.get_se(base_speaker, tone_color_converter, vad=vad_select)
+        target_se, _ = se_extractor.get_se(reference_speaker, tone_color_converter, vad=vad_select)
+        
+        # Define output file paths
+        save_path = f'{output_dir}/output_cloned.wav'
+        
+        # Perform tone color conversion
+        tone_color_converter.convert(
+            audio_src_path=base_speaker, 
+            src_se=source_se, 
+            tgt_se=target_se, 
+            output_path=save_path,
+        )
+        return save_path, "Voice cloning successful!"
+    except Exception as e:
+        return None, f"Error: {str(e)}"
+
+def ui_fn(text, model_dir, model_name, clone, reference_speaker, model_version, device_choice, vad_select):
+    model_path = os.path.join(model_dir, model_name)
+    sampling_rate, audio_data = generate_speech(text, model_path)
+    audio_file = save_audio(sampling_rate, audio_data)
+    
+    if clone:
+        cloned_audio_file, status = voice_cloning(audio_file, reference_speaker, model_version, device_choice, vad_select)
+        return cloned_audio_file, status
+    else:
+        return audio_file, "Speech generation successful!"
+
+if __name__ == "__main__":
+    #model_dir = "./models_mms"
+    #model_names = get_model_names(model_dir)
+    
+    iface = gr.Interface(
+        fn=ui_fn,
+        inputs=[
+            gr.Textbox(label="Text to Synthesize"),
+            gr.Textbox(label="Model Path or Id", value="VIZINTZOR/MMS-TTS-THAI-MALE-NARRATOR"),
+            #gr.Dropdown(model_names, label="Model"),
+            gr.Checkbox(label="Clone Voice", value=False),
+            gr.Audio(label="Reference Speaker (Target Voice)", type="filepath"),
+            gr.Dropdown(["v1", "v2"], value="v2", label="Model Version"),
+            gr.Dropdown(["CPU", "GPU"], value="GPU" if torch.cuda.is_available() else "CPU", label="Device"),
+            gr.Checkbox(value=False, label="VAD", interactive=True)
+        ],
+        outputs=[
+            gr.Audio(label="Generated Audio", type="filepath"),
+            gr.Textbox(label="Status", interactive=False)
+        ],
+        title="Text-to-Speech Synthesizer with Voice Cloning",
+        description="Enter text and model path to generate speech. Optionally, clone the voice using a reference speaker."
+    )
+    iface.launch()