Create app_simple.py

app_simple.py

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+import os
+import sys
+import gradio as gr
+import numpy as np
+import subprocess
+import scipy.io.wavfile
+from pathlib import Path
+
+# Ensure the repository is cloned
+REPO_URL = "https://github.com/hpbyte/myanmar-tts.git"
+REPO_DIR = "myanmar-tts"
+
+def setup():
+    """Set up the environment by cloning the repository if needed."""
+    if not os.path.exists(REPO_DIR):
+        print(f"Cloning {REPO_URL}...")
+        subprocess.run(["git", "clone", REPO_URL], check=True)
+    
+    # Add the repository to Python path
+    repo_path = os.path.abspath(REPO_DIR)
+    if repo_path not in sys.path:
+        sys.path.append(repo_path)
+    
+    # Create model directory if it doesn't exist
+    if not os.path.exists("trained_model"):
+        os.makedirs("trained_model")
+
+def text_to_speech(text):
+    """Convert text to speech using Myanmar TTS."""
+    if not text.strip():
+        return None, "Please enter some text."
+    
+    try:
+        # Try to import the necessary modules
+        try:
+            import torch
+            from text import text_to_sequence
+            from utils.hparams import create_hparams
+            from train import load_model
+            from synthesis import generate_speech
+        except ImportError:
+            # If direct import fails, try to import from the local module
+            import torch
+            from myanmar_tts import synthesize
+            
+            # Use the simplified wrapper function
+            waveform, sample_rate = synthesize(text)
+            output_path = "output.wav"
+            scipy.io.wavfile.write(output_path, sample_rate, waveform)
+            return output_path, "Speech generated successfully!"
+        
+        # If direct import worked, continue with standard approach
+        checkpoint_path = os.path.join("trained_model", "checkpoint_latest.pth.tar")
+        config_path = os.path.join("trained_model", "hparams.yml")
+        
+        if not os.path.exists(checkpoint_path) or not os.path.exists(config_path):
+            return None, f"""Model files not found. Please upload:
+1. The checkpoint file to: {checkpoint_path}
+2. The hparams.yml file to: {config_path}
+
+You can obtain these files from the original repository."""
+        
+        # Load model and hyperparameters
+        hparams = create_hparams(config_path)
+        model = load_model(hparams)
+        model.load_state_dict(torch.load(checkpoint_path, map_location=torch.device('cpu'))['state_dict'])
+        model.eval()
+        
+        # Process text input
+        sequence = np.array(text_to_sequence(text, ['burmese_cleaners']))[None, :]
+        sequence = torch.autograd.Variable(torch.from_numpy(sequence)).cpu().long()
+        
+        # Generate mel spectrograms
+        mel_outputs, mel_outputs_postnet, _, alignments = model.inference(sequence)
+        
+        # Generate waveform
+        with torch.no_grad():
+            waveform = generate_speech(mel_outputs_postnet, hparams)
+        
+        # Save and return the audio
+        output_path = "output.wav"
+        scipy.io.wavfile.write(output_path, hparams.sampling_rate, waveform)
+        
+        return output_path, "Speech generated successfully!"
+        
+    except Exception as e:
+        error_msg = str(e)
+        detailed_msg = f"""Error: {error_msg}
+
+Make sure you have:
+1. Uploaded the model files to the 'trained_model' directory
+2. The files are correctly named 'checkpoint_latest.pth.tar' and 'hparams.yml'
+
+If you're still seeing this error, please check the repository for any specific setup instructions."""
+        
+        return None, detailed_msg
+
+# Set up the environment
+setup()
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=text_to_speech,
+    inputs=[
+        gr.Textbox(
+            lines=3, 
+            placeholder="Enter Burmese text here...", 
+            label="Text"
+        )
+    ],
+    outputs=[
+        gr.Audio(label="Generated Speech"),
+        gr.Textbox(label="Status", max_lines=10)
+    ],
+    title="Myanmar (Burmese) Text-to-Speech",
+    description="""
+    This is a demo of the Myanmar Text-to-Speech system developed by hpbyte.
+    Enter Burmese text in the box below and click 'Submit' to generate speech.
+    
+    **Important**: You need to upload the model files to the 'trained_model' directory:
+    - checkpoint_latest.pth.tar (the model checkpoint)
+    - hparams.yml (hyperparameters configuration)
+    
+    Source: [GitHub Repository](https://github.com/hpbyte/myanmar-tts)
+    """,
+    examples=[
+        ["မင်္ဂလာပါ"],
+        ["မြန်မာစကားပြောစနစ်ကို ကြိုဆိုပါတယ်"],
+        ["ဒီစနစ်ဟာ မြန်မာစာကို အသံအဖြစ် ပြောင်းပေးနိုင်ပါတယ်"],
+    ]
+)
+
+if __name__ == "__main__":
+    demo.launch()