emotional app

app.py

@@ -1,43 +1,83 @@
 import gradio as gr
 import numpy as np
+import time
+from datetime import datetime
 
-class AudioProcessor:
+class EmotionRecognizer:
     def __init__(self):
         self.sample_rate = 16000
+        self.emotion_history = []
+        
+    def analyze_audio(self, audio_data):
+        # Mock audio analysis - replace with your actual model
+        emotions = {
+            'happy': np.random.random() * 0.5,
+            'sad': np.random.random() * 0.3,
+            'angry': np.random.random() * 0.2,
+            'neutral': np.random.random() * 0.5
+        }
+        return emotions
+    
+    def analyze_image(self, image):
+        # Mock image analysis - replace with your actual model
+        emotions = {
+            'happy': np.random.random() * 0.6,
+            'confused': np.random.random() * 0.4,
+            'pain': np.random.random() * 0.3,
+            'neutral': np.random.random() * 0.5
+        }
+        return emotions
     
-    def process_audio(self, audio_input):
-        # This now has properly matched parentheses
-        return (np.random.random(self.sample_rate * 3), self.sample_rate)  # Both parentheses are closed
+    def process_inputs(self, video_frame, audio_data):
+        # Get current timestamp
+        timestamp = datetime.now().strftime("%H:%M:%S")
+        
+        # Process inputs (mock implementation)
+        audio_emotions = self.analyze_audio(audio_data) if audio_data else {}
+        visual_emotions = self.analyze_image(video_frame) if video_frame else {}
+        
+        # Combine results
+        combined = {**audio_emotions, **visual_emotions}
+        self.emotion_history.append((timestamp, combined))
+        
+        # Generate outputs
+        top_emotion = max(combined.items(), key=lambda x: x[1]) if combined else ('none', 0)
+        stats = f"Top emotion: {top_emotion[0]} ({top_emotion[1]:.2f})"
+        history = "\n".join([f"{t}: {e}" for t, e in self.emotion_history[-3:]])
+        
+        return stats, history
 
 def create_interface():
-    processor = AudioProcessor()
+    recognizer = EmotionRecognizer()
     
-    def process_audio(audio):
+    def process_frame(video_frame, audio_data):
         try:
-            audio_data, sr = processor.process_audio(audio)
-            status_msg = f"Processed {len(audio_data)} samples"
-            info_msg = f"{sr}Hz, {len(audio_data)/sr:.2f} seconds"
-            return status_msg, info_msg  # Two separate strings
+            stats, history = recognizer.process_inputs(video_frame, audio_data)
+            return stats, history
         except Exception as e:
-            return f"Error: {str(e)}", "No info available"  # Still two values
+            return f"Error: {str(e)}", "No history available"
     
-    with gr.Blocks() as demo:
-        gr.Markdown("## Fixed Audio Processor")
-        
-        mic = gr.Audio(sources=["microphone"], type="filepath")
-        btn = gr.Button("Process Audio")
+    with gr.Blocks(title="Emotion Recognition", theme=gr.themes.Soft()) as app:
+        gr.Markdown("# Patient Emotion Recognition System")
         
-        status = gr.Textbox(label="Status")
-        info = gr.Textbox(label="Audio Info")
+        with gr.Row():
+            with gr.Column():
+                video_input = gr.Image(sources=["webcam"], label="Video Feed")
+                audio_input = gr.Audio(sources=["microphone"], label="Audio Input")
+                process_btn = gr.Button("Analyze", variant="primary")
+            
+            with gr.Column():
+                stats_output = gr.Textbox(label="Current Analysis")
+                history_output = gr.Textbox(label="Recent History", lines=4)
         
-        btn.click(
-            fn=process_audio,
-            inputs=[mic],
-            outputs=[status, info]
+        process_btn.click(
+            fn=process_frame,
+            inputs=[video_input, audio_input],
+            outputs=[stats_output, history_output]
         )
     
-    return demo
+    return app
 
 if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch()
+    app = create_interface()
+    app.launch()