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Update app.py
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app.py
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import gradio as gr
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import cv2
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import random
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from services.video_service import get_random_video_frame
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from services.overlay_service import overlay_boxes
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from services.detection_service import detect_objects
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from services.thermal_service import detect_thermal_anomalies
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# Constants
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TEMP_IMAGE_PATH = "
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#
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frame_rate = 1 # default frame rate in seconds
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#
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detections = detect_objects(TEMP_IMAGE_PATH)
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thermal_detections = detect_thermal_anomalies(TEMP_IMAGE_PATH)
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# Merge all detections
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combined_detections = detections + thermal_detections
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# Overlay the detections
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annotated_frame = overlay_boxes(frame.copy(), combined_detections)
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# Update status text
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status_text = f"Active Anomaly: {anomaly_type} | Objects Detected: {len(detections)} | Thermal Alerts: {len(thermal_detections)}"
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return annotated_frame, status_text
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def loop_monitor():
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global paused
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while True:
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if not paused:
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# Pause/Resume control
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def toggle_pause():
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paused
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return "Resume" if paused else "Pause"
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# Frame Rate control
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def update_frame_rate(new_rate):
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global frame_rate
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frame_rate = new_rate
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return f"Frame Rate set to {new_rate} sec"
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# Build Gradio Interface
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def build_interface():
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with gr.Blocks() as app:
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with gr.Row():
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video_output = gr.Image(label="
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metrics_output = gr.Textbox(label="Live Metrics"
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with gr.Row():
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pause_button = gr.Button("Pause")
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frame_rate_slider = gr.Slider(minimum=0.5, maximum=5, value=1, step=0.5, label="Frame Update Interval (seconds)")
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# Pause/Resume button logic
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pause_button.click(toggle_pause, outputs=pause_button)
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# Frame Rate Slider logic
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frame_rate_slider.change(update_frame_rate, inputs=frame_rate_slider, outputs=None)
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return app
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demo = build_interface()
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demo.launch()
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import gradio as gr
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import cv2
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import os
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import random
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import time
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from services.video_service import get_random_video_frame
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from services.overlay_service import overlay_boxes
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# Constants
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TEMP_IMAGE_PATH = "temp_frame.jpg"
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VIDEOS_FOLDER = "videos"
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# App states
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app_state = {"paused": False}
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# Live metrics
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live_metrics = {
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"Frames Processed": 0,
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"Current FPS": 1,
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"Detections": 0,
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}
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def monitor_feed(frame_rate=1):
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while True:
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if not app_state["paused"]:
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frame, label = get_random_video_frame()
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if frame is not None:
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frame_with_overlay = overlay_boxes(frame, label)
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cv2.imwrite(TEMP_IMAGE_PATH, frame_with_overlay)
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live_metrics["Frames Processed"] += 1
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live_metrics["Current FPS"] = frame_rate
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else:
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continue # Skip if frame is None
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time.sleep(1.0 / frame_rate)
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yield TEMP_IMAGE_PATH, format_metrics()
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def format_metrics():
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return (f"Frames Processed: {live_metrics['Frames Processed']}\n"
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f"Current FPS: {live_metrics['Current FPS']}\n"
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f"Detections: {live_metrics['Detections']}")
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def toggle_pause():
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app_state["paused"] = not app_state["paused"]
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return "鈻讹笍 Resume" if app_state["paused"] else "鈴革笍 Pause"
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def build_interface():
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with gr.Blocks() as app:
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gr.Markdown("# Solar Surveillance System \ud83c\udf0c")
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with gr.Row():
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video_output = gr.Image(label="Live Feed", elem_id="video-stream")
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metrics_output = gr.Textbox(label="Live Metrics")
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with gr.Row():
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with gr.Column():
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pause_button = gr.Button("鈴革笍 Pause")
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frame_slider = gr.Slider(1, 10, value=1, step=1, label="Frame Rate (FPS)")
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runner = gr.Interface(
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fn=monitor_feed,
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inputs=frame_slider,
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outputs=[video_output, metrics_output],
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live=True,
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concurrency_limit=1
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)
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pause_button.click(toggle_pause, outputs=pause_button)
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return app
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if __name__ == "__main__":
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demo = build_interface()
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demo.launch()
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