Update services/thermal_service.py

services/thermal_service.py

@@ -1,17 +1,18 @@
-import torch
-import numpy as np
+import torch  # Import PyTorch for tensor operations
+import numpy as np  # Import NumPy for array handling
 
+# Function to detect hotspots (optional, for solar panels)
 def detect_hotspots(model, image):
-    img_tensor = torch.from_numpy(image).permute(2, 0, 1).float() / 255.0
-    img_tensor = img_tensor.unsqueeze(0)
+    img_tensor = torch.from_numpy(image).permute(2, 0, 1).float() / 255.0  # Convert image to tensor
+    img_tensor = img_tensor.unsqueeze(0)  # Add batch dimension
 
-    with torch.no_grad():
+    with torch.no_grad():  # Disable gradient tracking for inference
         results = model(img_tensor)
 
-    hotspots = []
-    for detection in results[0].boxes:
+    hotspots = []  # List to store detected hotspots
+    for detection in results[0].boxes:  # Iterate over detected objects
         class_id = int(detection.cls)
         if class_id == 4:
             hotspots.append({"type": "Hotspot", "location": (detection.xyxy[0][0].item(), detection.xyxy[0][1].item())})
 
-    return hotspots
+    return hotspots  # Return list of hotspots