Rename thermal_service.py to services/thermal_service.py

services/thermal_service.py

@@ -0,0 +1,9 @@
+import numpy as np
+import cv2
+
+# Simulate thermal anomaly by analyzing red channel brightness
+def detect_thermal_anomalies(image_path):
+    image = cv2.imread(image_path)
+    red_channel = image[:, :, 2]
+    avg_temp = red_channel.mean()
+    return avg_temp > 180  # Simulate overheat detection (like >75°C)

thermal_service.py

@@ -1,12 +0,0 @@
-from ultralytics import YOLO
-
-# Load thermal model
-thermal_model = YOLO("thermal_model.pt")  # You must upload your model here
-
-def detect_thermal_anomalies(image_path):
-    results = thermal_model(image_path)
-    flagged = []
-    for r in results:
-        if hasattr(r, 'temperature') and r.temperature > 75:
-            flagged.append(r)
-    return flagged