Update app.py

app.py

@@ -5,11 +5,10 @@ import cv2
 import os
 from services.video_service import get_video_frame
 from services.detection_service import detect_objects
-from services.thermal_service import detect_thermal_anomalies
+from services.thermal_service import detect_thermal_anomalies, overlay_thermal_boxes
 from services.shadow_detection import detect_shadow_coverage
 from services.salesforce_dispatcher import send_to_salesforce
 
-# Global frame generator
 frame_gen = get_video_frame("data/drone_day.mp4")
 
 def monitor_feed():
@@ -19,46 +18,24 @@ def monitor_feed():
         cv2.imwrite(temp_path, frame)
 
         detections = detect_objects(temp_path)
-        thermal_flags = detect_thermal_anomalies(temp_path)
+        thermal_boxes = detect_thermal_anomalies(temp_path)
         shadow_flag = detect_shadow_coverage(temp_path)
 
-        # Prepare alert payload
         alert_payload = {
             "detections": detections,
-            "thermal": bool(thermal_flags),
+            "thermal": bool(thermal_boxes),
             "shadow_issue": shadow_flag,
         }
         send_to_salesforce(alert_payload)
 
-        # Create human-readable alert
-        detected_classes = [d['label'] for d in detections]
-        confidence_scores = [round(d['score'] * 100, 2) for d in detections]
-        confidence_max = max(confidence_scores) if confidence_scores else 0
+        # Overlay thermal boxes
+        if thermal_boxes:
+            frame = overlay_thermal_boxes(temp_path, thermal_boxes)
 
-        alert_message = f"""
-        🚨 Detection Summary 🚨
-        Detected Objects: {', '.join(detected_classes) if detected_classes else 'None'}
-        Thermal Issue: {'Yes' if alert_payload['thermal'] else 'No'}
-        Shadow Issue: {'Yes' if alert_payload['shadow_issue'] else 'No'}
-        Highest Confidence: {confidence_max}%
-        """
-
-        # Return the frame and the alert
-        return frame, alert_message.strip()
+        return frame
 
     except StopIteration:
-        return None, "End of Video Feed."
-
-# 🎯 Create better Gradio Interface
-with gr.Blocks(title="Solar Surveillance Feed Simulation") as app:
-    gr.Markdown("# ☀️ Solar Site Live Surveillance")
-    gr.Markdown("### Live Drone Feed with AI Intrusion + Thermal + Shadow Monitoring")
-    
-    video_output = gr.Image(label="Drone Camera View", shape=(512, 512))
-    alert_output = gr.Textbox(label="AI Generated Alerts", lines=5)
-
-    live_button = gr.Button("Start Live Surveillance 🚀")
-
-    live_button.click(fn=monitor_feed, outputs=[video_output, alert_output])
+        return None
 
-app.queue().launch()
+iface = gr.Interface(fn=monitor_feed, inputs=[], outputs="image", live=True, title="Solar Surveillance Feed Simulation")
+iface.launch()