Fix logo paths and layout proportions, clean duplicate files

app.py

@@ -964,19 +964,18 @@ def create_interface():
         
         # Logos section
         with gr.Row():
-            with gr.Column():
-                gr.HTML("""
-                <div style="display: flex; justify-content: center; align-items: center; gap: 20px; margin: 20px 0; flex-wrap: wrap;">
-                    <img src="file/ai4s_banner.png" alt="AI4S" style="height: 60px; object-fit: contain;">
-                    <img src="file/surrey_logo.png" alt="University of Surrey" style="height: 60px; object-fit: contain;">
-                    <img src="file/EPSRC_logo.png" alt="EPSRC" style="height: 60px; object-fit: contain;">
-                    <img src="file/CVSSP_logo.png" alt="CVSSP" style="height: 60px; object-fit: contain;">
-                </div>
-                """)
+            gr.HTML("""
+            <div style="display: flex; justify-content: center; align-items: center; gap: 30px; margin: 20px 0; flex-wrap: wrap;">
+                <img src="ai4s_banner.png" alt="AI4S" style="height: 60px; object-fit: contain;">
+                <img src="surrey_logo.png" alt="University of Surrey" style="height: 60px; object-fit: contain;">
+                <img src="EPSRC_logo.png" alt="EPSRC" style="height: 60px; object-fit: contain;">
+                <img src="CVSSP_logo.png" alt="CVSSP" style="height: 60px; object-fit: contain;">
+            </div>
+            """)
         
         # Main interface
         with gr.Row():
-            with gr.Column(scale=1):
+            with gr.Column(scale=2):
                 gr.Markdown("### 🎛️ Controls")
                 
                 audio_input = gr.Audio(
@@ -1007,11 +1006,12 @@ def create_interface():
                 
                 process_btn = gr.Button("🎤 Analyze", variant="primary", size="lg")
                 
-            with gr.Column(scale=2):
+            with gr.Column(scale=3):
                 status_display = gr.Textbox(
                     label="Status",
                     value="🔇 Ready to analyze audio",
-                    interactive=False
+                    interactive=False,
+                    lines=2
                 )
         
         # Results

app_fixed.py

@@ -1,119 +0,0 @@
-import gradio as gr
-import numpy as np
-import torch
-import torch.nn.functional as F
-try:
-    import librosa
-    LIBROSA_AVAILABLE = True
-except ImportError:
-    LIBROSA_AVAILABLE = False
-    print("⚠️ Librosa not available, using scipy fallback")
-
-import plotly.graph_objects as go
-from plotly.subplots import make_subplots
-import io
-import time
-from typing import Dict, Tuple, Optional
-import threading
-import queue
-from dataclasses import dataclass
-from collections import deque
-
-# Resto del código igual hasta la función create_interface...
-# [Aquí iría todo el código de las clases como está, pero cambio solo la parte del streaming]
-
-def create_interface():
-    """Create Gradio interface with corrected streaming"""
-    
-    with gr.Blocks(title="VAD Demo - Real-time Speech Detection", theme=gr.themes.Soft()) as interface:
-        gr.Markdown("""
-        # 🎤 VAD Demo: Real-time Speech Detection Framework
-        
-        **Multi-Model Voice Activity Detection with Interactive Visualization**
-        
-        This demo showcases 5 different AI models for speech detection optimized for CPU.
-        """)
-        
-        with gr.Row():
-            with gr.Column(scale=1):
-                gr.Markdown("### 🎛️ **Controls**")
-                
-                model_a = gr.Dropdown(
-                    choices=list(demo_app.models.keys()),
-                    value="Silero-VAD",
-                    label="Panel A Model"
-                )
-                
-                model_b = gr.Dropdown(
-                    choices=list(demo_app.models.keys()),
-                    value="E-PANNs", 
-                    label="Panel B Model"
-                )
-                
-                threshold_slider = gr.Slider(
-                    minimum=0.0,
-                    maximum=1.0,
-                    value=0.5,
-                    step=0.05,
-                    label="Detection Threshold"
-                )
-                
-                status_display = gr.Textbox(
-                    label="Status",
-                    value="🔇 Ready to detect speech",
-                    interactive=False
-                )
-            
-            with gr.Column(scale=2):
-                gr.Markdown("### 🎙️ **Audio Input**")
-                
-                # Simplified audio input without streaming for compatibility
-                audio_input = gr.Audio(
-                    sources=["microphone"],
-                    type="numpy",
-                    label="Microphone Input"
-                )
-                
-                process_btn = gr.Button("🎯 Process Audio", variant="primary")
-                
-                gr.Markdown("### 📊 **Analysis Results**")
-                
-                plot_output = gr.Plot(label="VAD Analysis")
-                model_details = gr.JSON(label="Model Details")
-        
-        # Event handlers - usando click en lugar de streaming para compatibilidad
-        process_btn.click(
-            fn=demo_app.process_audio_stream,
-            inputs=[audio_input, model_a, model_b, threshold_slider],
-            outputs=[plot_output, status_display, model_details]
-        )
-        
-        # Auto-process cuando se graba audio
-        audio_input.change(
-            fn=demo_app.process_audio_stream,
-            inputs=[audio_input, model_a, model_b, threshold_slider],
-            outputs=[plot_output, status_display, model_details]
-        )
-        
-        gr.Markdown("""
-        ### 🔬 **Research Context**
-        This demonstration supports research in privacy-preserving audio datasets and real-time speech analysis.
-        Original: https://github.com/gbibbo/vad_demo
-        """)
-    
-    return interface
-
-# Initialize demo
-demo_app = VADDemo()
-
-# Create and launch interface
-if __name__ == "__main__":
-    interface = create_interface()
-    interface.queue(max_size=20)
-    
-    # Simplified launch for HF Spaces compatibility
-    interface.launch(
-        share=False,  # HF Spaces maneja esto automáticamente
-        debug=False,
-        show_error=True
-    )