Create thermal_service.py

services/thermal_service.py

@@ -0,0 +1,46 @@
+# services/thermal_service.py
+import cv2
+import numpy as np
+
+def process_thermal(frame):
+    """
+    Process thermal camera data to detect hot spots.
+    Args:
+        frame: Input frame (grayscale, representing temperature)
+    Returns:
+        dict: Hot spot detection results with numbered labels
+        numpy array: 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}