Update services/thermal_service.py

services/thermal_service.py

@@ -1,46 +1,62 @@
-# services/thermal_service.py
 import cv2
 import numpy as np
+import logging
+
+# Setup logging
+logging.basicConfig(
+    filename="app.log",
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s"
+)
 
 def process_thermal(frame):
     """
-    Process thermal camera data to detect hot spots.
+    Process a thermal (grayscale) frame to detect hot/cold spots.
     Args:
-        frame: Input frame (grayscale, representing temperature)
+        frame: Input frame (grayscale numpy array)
     Returns:
-        dict: Hot spot detection results with numbered labels
-        numpy array: Annotated frame
+        dict: Results with detections and annotated frame
     """
-    # Apply thresholding to detect hot spots (high temperature areas)
-    _, hot_mask = cv2.threshold(frame, 200, 255, cv2.THRESH_BINARY)
-    contours, _ = cv2.findContours(hot_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-    detections = []
-    line_counter = 1  # Initialize counter for numbered labels
-
-    # Convert frame to BGR for annotations
-    frame_bgr = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)
-
-    for contour in contours:
-        area = cv2.contourArea(contour)
-        if area < 50:  # Filter small areas
-            continue
-        x, y, w, h = cv2.boundingRect(contour)
-        x_min, y_min, x_max, y_max = x, y, x + w, y + h
-
-        # Add numbered label
-        detection_label = f"Line {line_counter} - Hot Spot"
-        detections.append({
-            "label": detection_label,
-            "coordinates": [x_min, y_min, x_max, y_max]
-        })
-
-        # Draw bounding box and label
-        color = (255, 0, 0)  # Red for hot spots
-        cv2.rectangle(frame_bgr, (x_min, y_min), (x_max, y_max), color, 2)
-        cv2.putText(frame_bgr, detection_label, (x_min, y_min - 10), 
-                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
-        
-        line_counter += 1
-
-    return {"detections": detections, "frame": frame_bgr}
+    try:
+        # Ensure frame is grayscale
+        if len(frame.shape) == 3:
+            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+        # Threshold to detect hot spots (high intensity)
+        _, hot_mask = cv2.threshold(frame, 200, 255, cv2.THRESH_BINARY)
+        contours, _ = cv2.findContours(hot_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        # Convert grayscale to BGR for annotation
+        frame_bgr = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)
+
+        detections = []
+        line_counter = 1  # Initialize counter for numbered labels
+
+        for contour in contours:
+            area = cv2.contourArea(contour)
+            if area < 200:  # Filter small areas
+                continue
+            x, y, w, h = cv2.boundingRect(contour)
+            x_min, y_min, x_max, y_max = x, y, x + w, y + h
+
+            # Add numbered label
+            detection_label = f"Line {line_counter} - Hot Spot"
+            detections.append({
+                "type": "hot_spot",
+                "label": detection_label,
+                "coordinates": [x_min, y_min, x_max, y_max]
+            })
+
+            # Draw bounding box and label
+            color = (255, 69, 0)  # OrangeRed for hot spots
+            cv2.rectangle(frame_bgr, (x_min, y_min), (x_max, y_max), color, 2)
+            cv2.putText(frame_bgr, detection_label, (x_min, y_min - 10), 
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+            
+            line_counter += 1
+
+        logging.info(f"Detected {len(detections)} hot spots in thermal frame.")
+        return {"detections": detections, "frame": frame_bgr}
+    except Exception as e:
+        logging.error(f"Error processing thermal frame: {str(e)}")
+        return {"detections": [], "frame": frame}