Fix minor issues

modules/detect_target/detect_target_brightspot.py

@@ -1,5 +1,5 @@
 """
-Detects bright spots generated by an IR camera.
+Detects bright spots in images.
 """
 
 import time
@@ -8,14 +8,16 @@
 import numpy as np
 
 from . import base_detect_target
-from .. import image_and_time
 from .. import detections_and_time
+from .. import image_and_time
 from ..common.modules.logger import logger
 
 
 BRIGHTSPOT_PERCENTILE = 99.9
+
+# Label for brightspots
 DETECTION_LABEL = 1
-# Confidence set to 1 by default because SimpleBlobDetector does not compute a reponse value during keypoint detection
+# SimpleBlobDetector is a binary detector, so a detection has confidence 1.0 by default
 CONFIDENCE = 1
 
 
@@ -45,7 +47,7 @@ def __init__(
 
     def run(
         self, data: image_and_time.ImageAndTime
-    ) -> "tuple[bool, detections_and_time.DetectionsAndTime | None]":
+    ) -> "tuple[True, detections_and_time.DetectionsAndTime] | tuple[False, None]":
         """
         Runs brightspot detection on the provided image and returns the detections.
 
@@ -57,19 +59,20 @@ def run(
 
         image = data.image
         try:
-            gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+            grey_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
         # Catching all exceptions for library call
         # pylint: disable-next=broad-exception-caught
         except Exception as exception:
-            self.__local_logger.error(f"{time.time()}: Failed to convert to grayscale.")
-            self.__local_logger.error(f"{exception}")
+            self.__local_logger.error(
+                f"{time.time()}: Failed to convert to greyscale, exception: {exception}"
+            )
             return False, None
 
-        brightspot_threshold = np.percentile(gray_image, BRIGHTSPOT_PERCENTILE)
+        brightspot_threshold = np.percentile(grey_image, BRIGHTSPOT_PERCENTILE)
 
         # Apply thresholding to isolate bright spots
         threshold_used, bw_image = cv2.threshold(
-            gray_image, brightspot_threshold, 255, cv2.THRESH_BINARY
+            grey_image, brightspot_threshold, 255, cv2.THRESH_BINARY
         )
         if threshold_used == 0:
             self.__local_logger.error(f"{time.time()}: Failed to threshold image.")
@@ -84,7 +87,7 @@ def run(
         params.minInertiaRatio = 0.2
         params.filterByConvexity = False
         params.filterByArea = True
-        params.minArea = 50
+        params.minArea = 50  # pixels
         detector = cv2.SimpleBlobDetector_create(params)
         keypoints = detector.detect(bw_image)
         if len(keypoints) == 0:
@@ -93,12 +96,13 @@ def run(
 
         # Annotate the image (green circle) with detected keypoints
         image_annotated = cv2.drawKeypoints(
-            image, keypoints, np.array([]), (0, 255, 0), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS
+            image, keypoints, None, (0, 255, 0), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS
         )
 
         # Process bright spot detection
         result, detections = detections_and_time.DetectionsAndTime.create(data.timestamp)
         if not result:
+            self.__local_logger.error(f"{time.time()}: Failed to create detections for image.")
             return False, None
 
         # Get Pylance to stop complaining
@@ -112,12 +116,16 @@ def run(
             result, detection = detections_and_time.Detection.create(
                 bounds, DETECTION_LABEL, CONFIDENCE
             )
-            if result:
-                # Get Pylance to stop complaining
-                assert detections is not None
+            if not result:
+                self.__local_logger.error(f"{time.time()}: Failed to create bounding boxes.")
+                return False, None
+
+            # Get Pylance to stop complaining
+            assert detections is not None
 
-                detections.append(detection)
+            detections.append(detection)
 
+        # Logging is identical to detect_target_ultralytics
         # pylint: disable=duplicate-code
         end_time = time.time()
 
@@ -137,4 +145,6 @@ def run(
         if self.__show_annotations:
             cv2.imshow("Annotated", image_annotated)  # type: ignore
 
+        # pylint: enable=duplicate-code
+
         return True, detections

tests/brightspot_example/generate_expected.py

@@ -7,14 +7,14 @@
 import cv2
 import numpy as np
 
-from modules.detect_target import detect_target_brightspot
 from modules import image_and_time
 from modules.common.modules.logger import logger
+from modules.detect_target import detect_target_brightspot
 
 
 NUMBER_OF_IMAGES = 7
 TEST_PATH = pathlib.Path("tests", "brightspot_example")
-IMAGE_FILES = [f"ir{i}.png" for i in range(1, NUMBER_OF_IMAGES + 1)]
+IMAGE_FILES = [pathlib.Path(f"ir{i}.png") for i in range(1, NUMBER_OF_IMAGES + 1)]
 ANNOTATED_IMAGE_PATHS = [
     pathlib.Path(TEST_PATH, f"ir{i}_annotated.png") for i in range(1, NUMBER_OF_IMAGES + 1)
 ]
@@ -42,15 +42,21 @@ def main() -> int:
         image_path = pathlib.Path(TEST_PATH, image_file)
         image = cv2.imread(str(image_path))  # type: ignore
         result, image_data = image_and_time.ImageAndTime.create(image)
-        if not result or image_data is None:
-            print(f"Failed to load image {image_path}.")
+        if not result:
+            temp_logger.error(f"Failed to load image {image_path}.")
             continue
 
-        success, detections = detector.run(image_data)
-        if not success or detections is None:
-            print(f"Detection failed or returned no detections for {image_path}.")
+        # Get Pylance to stop complaining
+        assert image_data is not None
+
+        result, detections = detector.run(image_data)
+        if not result:
+            temp_logger.error(f"Detection failed or returned no detections for {image_path}.")
             continue
 
+        # Get Pylance to stop complaining
+        assert detections is not None
+
         detections_list = []
         image_annotated = image.copy()
         for detection in detections.detections:
@@ -67,10 +73,14 @@ def main() -> int:
         detections_array = np.array(detections_list)
 
         np.savetxt(expected_detections_path, detections_array, fmt="%.6f")
-        print(f"Expected detections saved to {expected_detections_path}")
+        temp_logger.info(f"Expected detections saved to {expected_detections_path}.")
+
+        result = cv2.imwrite(str(annotated_image_path), image_annotated)  # type: ignore
+        if not result:
+            temp_logger.error(f"Failed to wrtie image to {annotated_image_path}.")
+            continue
 
-        cv2.imwrite(str(annotated_image_path), image_annotated)  # type: ignore
-        print(f"Annotated image saved to {annotated_image_path}")
+        temp_logger.info(f"Annotated image saved to {annotated_image_path}.")
 
     return 0