Update app.py

app.py

@@ -1,11 +1,11 @@
 import gradio as gr
 import cv2
 import os
+import time
 from services.video_service import get_random_video_frame
 from services.thermal_service import detect_thermal_anomalies
 from services.overlay_service import overlay_boxes
 from services.metrics_service import update_metrics
-import time
 
 # Globals
 paused = False
@@ -18,20 +18,24 @@ TEMP_IMAGE_PATH = "temp.jpg"
 def monitor_feed():
     global paused
 
-    while True:
-        if paused:
+    frame = None
+
+    if paused:
+        if os.path.exists(TEMP_IMAGE_PATH):
             frame = cv2.imread(TEMP_IMAGE_PATH)
-            if frame is None:
-                frame = get_random_video_frame()
-        else:
-            frame = get_random_video_frame()
-            detected_boxes = detect_thermal_anomalies(frame)
-            frame = overlay_boxes(frame, detected_boxes)
-            cv2.imwrite(TEMP_IMAGE_PATH, frame)
-
-        metrics = update_metrics()
-        yield frame[:, :, ::-1], metrics  # Convert BGR to RGB for Gradio
-        time.sleep(frame_rate)
+
+    if frame is None:
+        frame = get_random_video_frame()
+
+    if not paused:
+        detected_boxes = detect_thermal_anomalies(frame)
+        frame = overlay_boxes(frame, detected_boxes)
+        cv2.imwrite(TEMP_IMAGE_PATH, frame)
+        metrics = update_metrics(detected_boxes)
+    else:
+        metrics = update_metrics([])
+
+    return frame[:, :, ::-1], metrics  # BGR to RGB
 
 # Gradio UI
 with gr.Blocks() as app:
@@ -64,7 +68,14 @@ with gr.Blocks() as app:
     resume_btn.click(toggle_resume)
     frame_slider.change(set_frame_rate, inputs=[frame_slider])
 
-    app.load(monitor_feed, outputs=[video_output, metrics_output])
+    def streaming_loop():
+        while True:
+            frame, metrics = monitor_feed()
+            video_output.update(value=frame)
+            metrics_output.update(value=metrics)
+            time.sleep(frame_rate)
+
+    app.load(streaming_loop)
 
 if __name__ == "__main__":
     app.launch()