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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
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from services.video_service import get_video_frame
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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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from services.shadow_detection import detect_shadow_coverage
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from services.salesforce_dispatcher import send_to_salesforce
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#
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#
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def monitor_feed():
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try:
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frame = next(frame_gen)
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temp_path = "temp
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cv2.imwrite(temp_path, frame)
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# Object Detection
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detections = detect_objects(temp_path)
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# Thermal Detection
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thermal_boxes = detect_thermal_anomalies(temp_path)
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# Shadow Detection
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shadow_flag = detect_shadow_coverage(temp_path)
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# Draw bounding boxes for visualization
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for d in detections:
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box = d['box']
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label = d['label']
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score = d['score']
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x0, y0, x1, y1 = int(box['xmin']), int(box['ymin']), int(box['xmax']), int(box['ymax'])
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cv2.rectangle(frame, (x0, y0), (x1, y1), (0, 255, 0), 2)
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cv2.putText(frame, f"{label} {score:.2f}", (x0, y0-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
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for box in thermal_boxes:
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x0, y0, x1, y1 = int(box['xmin']), int(box['ymin']), int(box['xmax']), int(box['ymax'])
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cv2.rectangle(frame, (x0, y0), (x1, y1), (0, 0, 255), 2)
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cv2.putText(frame, "Thermal", (x0, y1+20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
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# Prepare payload to send
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alert_payload = {
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"detections": detections,
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"thermal": bool(thermal_boxes),
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"shadow_issue": shadow_flag,
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}
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# send_to_salesforce(alert_payload)
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# ⚠️ TODO: Update SALESFORCE_WEBHOOK_URL in salesforce_dispatcher.py
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return frame
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except StopIteration:
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return None
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# Build Gradio UI
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iface = gr.Interface(
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fn=monitor_feed,
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inputs=[],
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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_video_frame
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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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from services.shadow_detection import detect_shadow_coverage
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from services.salesforce_dispatcher import send_to_salesforce
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# List of videos to cycle or pick randomly
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VIDEO_LIST = [
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"data/drone_day.mp4",
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"data/thermal_hotspot.mp4",
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"data/shadow_dust_issue.mp4",
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"data/alert_response.mp4",
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]
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# Pick a random video at app startup
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selected_video = random.choice(VIDEO_LIST)
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frame_gen = get_video_frame(selected_video)
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def monitor_feed():
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try:
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frame = next(frame_gen)
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if frame is None:
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return None
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temp_path = "temp.jpg"
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cv2.imwrite(temp_path, frame)
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detections = detect_objects(temp_path)
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thermal_boxes = detect_thermal_anomalies(temp_path)
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shadow_flag = detect_shadow_coverage(temp_path)
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alert_payload = {
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"detections": detections,
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"thermal": bool(thermal_boxes),
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"shadow_issue": shadow_flag,
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}
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send_to_salesforce(alert_payload)
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return frame
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except StopIteration:
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return None
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iface = gr.Interface(
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fn=monitor_feed,
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inputs=[],
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