Update services/shadow_detection.py

services/shadow_detection.py

@@ -1,45 +1,58 @@
-# services/shadow_detection.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 detect_shadows(frame):
     """
-    Detect shadows in a frame using basic image processing.
+    Detect shadows in a frame using brightness thresholding.
     Args:
         frame: Input frame (numpy array)
     Returns:
-        dict: Shadow detection results with numbered labels
-        numpy array: Annotated frame
+        dict: Results with detections and annotated frame
     """
-    # Convert to grayscale
-    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    # Apply thresholding to detect dark areas (potential shadows)
-    _, shadow_mask = cv2.threshold(gray, 50, 255, cv2.THRESH_BINARY_INV)
-    contours, _ = cv2.findContours(shadow_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-    detections = []
-    line_counter = 1  # Initialize counter for numbered labels
-
-    for contour in contours:
-        area = cv2.contourArea(contour)
-        if area < 100:  # 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} - Shadow"
-        detections.append({
-            "label": detection_label,
-            "coordinates": [x_min, y_min, x_max, y_max]
-        })
-
-        # Draw bounding box and label
-        color = (128, 128, 128)  # Gray for shadows
-        cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2)
-        cv2.putText(frame, detection_label, (x_min, y_min - 10), 
-                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
-        
-        line_counter += 1
-
-    return {"detections": detections, "frame": frame}
+    try:
+        # Convert to grayscale
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+        # Threshold to detect dark areas (shadows)
+        _, shadow_mask = cv2.threshold(gray, 50, 255, cv2.THRESH_BINARY_INV)
+        contours, _ = cv2.findContours(shadow_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        detections = []
+        line_counter = 1  # Initialize counter for numbered labels
+
+        for contour in contours:
+            area = cv2.contourArea(contour)
+            if area < 500:  # 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} - Shadow"
+            detections.append({
+                "type": "shadow",
+                "label": detection_label,
+                "coordinates": [x_min, y_min, x_max, y_max]
+            })
+
+            # Draw bounding box and label
+            color = (128, 128, 128)  # Gray for shadows
+            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), color, 2)
+            cv2.putText(frame, detection_label, (x_min, y_min - 10), 
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+            
+            line_counter += 1
+
+        logging.info(f"Detected {len(detections)} shadows in frame.")
+        return {"detections": detections, "frame": frame}
+    except Exception as e:
+        logging.error(f"Error detecting shadows: {str(e)}")
+        return {"detections": [], "frame": frame}