Update app.py

app.py

@@ -1,73 +1,78 @@
-import gradio as gr
-import cv2
 import os
+import cv2
 import random
 import time
+import gradio as gr
+import numpy as np
 from services.video_service import get_random_video_frame
 from services.overlay_service import overlay_boxes
 
 # Constants
-TEMP_IMAGE_PATH = "temp_frame.jpg"
-VIDEOS_FOLDER = "videos"
+TEMP_IMAGE_PATH = "temp.jpg"
 
-# App states
-app_state = {"paused": False}
+# Global control flags
+is_paused = False
+frame_rate = 1  # Default frame rate (frames per second)
 
-# Live metrics
-live_metrics = {
-    "Frames Processed": 0,
-    "Current FPS": 1,
-    "Detections": 0,
+# Live Metrics
+metrics = {
+    "total_frames": 0,
+    "detected_objects": 0,
 }
 
-def monitor_feed(frame_rate=1):
+def monitor_feed():
+    global is_paused, frame_rate, metrics
+
     while True:
-        if not app_state["paused"]:
-            frame, label = get_random_video_frame()
-            if frame is not None:
-                frame_with_overlay = overlay_boxes(frame, label)
-                cv2.imwrite(TEMP_IMAGE_PATH, frame_with_overlay)
-                live_metrics["Frames Processed"] += 1
-                live_metrics["Current FPS"] = frame_rate
-            else:
-                continue  # Skip if frame is None
-        time.sleep(1.0 / frame_rate)
-        yield TEMP_IMAGE_PATH, format_metrics()
-
-def format_metrics():
-    return (f"Frames Processed: {live_metrics['Frames Processed']}\n"
-            f"Current FPS: {live_metrics['Current FPS']}\n"
-            f"Detections: {live_metrics['Detections']}")
+        if not is_paused:
+            frame, anomaly_label = get_random_video_frame()
+
+            if frame is None:
+                time.sleep(1)
+                continue
+
+            # Overlay anomaly text
+            frame = overlay_boxes(frame, anomaly_label)
+
+            # Save temporary image
+            cv2.imwrite(TEMP_IMAGE_PATH, frame)
+
+            metrics["total_frames"] += 1
+            metrics["detected_objects"] += random.randint(1, 3)  # Simulated detection count
+
+            yield TEMP_IMAGE_PATH, f"Frames: {metrics['total_frames']}, Detections: {metrics['detected_objects']}"
+
+        time.sleep(1 / max(frame_rate, 1))
 
 def toggle_pause():
-    app_state["paused"] = not app_state["paused"]
-    return "▶️ Resume" if app_state["paused"] else "⏸️ Pause"
+    global is_paused
+    is_paused = not is_paused
+    return "Paused" if is_paused else "Running"
 
-def build_interface():
-    with gr.Blocks() as app:
-        gr.Markdown("# Solar Surveillance System \ud83c\udf0c")
+def set_frame_rate(new_rate):
+    global frame_rate
+    frame_rate = new_rate
+    return f"Frame Rate: {frame_rate} fps"
 
+def build_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("# Solar Surveillance POC")
+        
         with gr.Row():
-            video_output = gr.Image(label="Live Feed", elem_id="video-stream")
-            metrics_output = gr.Textbox(label="Live Metrics")
+            video_output = gr.Image(label="Live Feed")
+            metrics_output = gr.Label(label="Live Metrics")
 
         with gr.Row():
-            with gr.Column():
-                pause_button = gr.Button("⏸️ Pause")
-                frame_slider = gr.Slider(1, 10, value=1, step=1, label="Frame Rate (FPS)")
+            pause_button = gr.Button("Pause / Resume")
+            frame_rate_slider = gr.Slider(1, 10, value=1, label="Frame Rate (frames/sec)")
 
-        runner = gr.Interface(
-            fn=monitor_feed,
-            inputs=frame_slider,
-            outputs=[video_output, metrics_output],
-            live=True,
-            concurrency_limit=1
-        )
+        pause_button.click(toggle_pause, outputs=[])
+        frame_rate_slider.change(set_frame_rate, inputs=frame_rate_slider, outputs=[])
 
-        pause_button.click(toggle_pause, outputs=pause_button)
+        demo.load(monitor_feed, outputs=[video_output, metrics_output], every=None)
 
-    return app
+    return demo
 
 if __name__ == "__main__":
     demo = build_interface()
-    demo.launch()
+    demo.launch(share=True)  # Important for Hugging Face Spaces!