Update app.py

app.py

@@ -1,53 +1,32 @@
-import gradio as gr
-from transformers import DetrImageProcessor, DetrForObjectDetection
-import torch
+import gradio as gr
 import cv2
-import numpy as np
-from PIL import Image
+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.shadow_detection import detect_shadow_coverage
+from services.salesforce_dispatcher import send_to_salesforce
 
-# Load Hugging Face object detection model
-processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
-model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+frame_gen = get_video_frame("data/drone_day.mp4")
 
-def detect_intrusion(video_path):
-    cap = cv2.VideoCapture(video_path)
-    alerts = []
-    count = 0
-    while cap.isOpened() and count < 20:
-        ret, frame = cap.read()
-        if not ret:
-            break
-        image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
-        inputs = processor(images=image, return_tensors="pt")
-        outputs = model(**inputs)
-        target_sizes = torch.tensor([image.size[::-1]])
-        results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
-        for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
-            label_name = model.config.id2label[label.item()]
-            if label_name == "person":
-                alerts.append(f"Frame {count}: 🔴 Person Detected!")
-                break
-        count += 1
-    cap.release()
-    return "\n".join(alerts) if alerts else "✅ No intrusion detected."
+def monitor_feed():
+try:
+frame = next(frame_gen)
+cv2.imwrite(&quot;temp.jpg&quot;, frame)
+detections = detect_objects(&quot;temp.jpg&quot;)
+thermal = detect_thermal_anomalies(&quot;temp.jpg&quot;)
+shadow_flag = detect_shadow_coverage(&quot;temp.jpg&quot;)
 
-def detect_overheat(temp, humidity, solar_output):
-    if temp > 75:
-        return "🔥 Overheat Fault!"
-    elif humidity < 20 and solar_output < 300:
-        return "🌫️ Dust/Shade Fault!"
-    else:
-        return "✅ All Good"
+alert_payload = {
+&quot;detections&quot;: detections,
+&quot;thermal&quot;: bool(thermal),
+&quot;shadow_issue&quot;: shadow_flag,
+}
+send_to_salesforce(alert_payload)
+return frame
+except StopIteration:
 
-video_tab = gr.Interface(fn=detect_intrusion,
-                         inputs=gr.Video(label="Upload Video"),
-                         outputs=gr.Textbox(label="Intrusion Detection Alerts"))
+return None
 
-sensor_tab = gr.Interface(fn=detect_overheat,
-                          inputs=[gr.Number(label="Temperature (°C)"),
-                                  gr.Number(label="Humidity (%)"),
-                                  gr.Number(label="Solar Output (W)")],
-                          outputs=gr.Textbox(label="Sensor Fault Detection"))
-
-gr.TabbedInterface([video_tab, sensor_tab], ["Intrusion (Video)", "Sensor (Input)"]).launch()
+iface = gr.Interface(fn=monitor_feed, inputs=[], outputs=&quot;image&quot;, live=True, title=&quot;Solar
+Surveillance Feed Simulation&quot;)