Catching an error in RDE around zero-pixel bounding boxes

api/batch_processing/postprocessing/repeat_detection_elimination/repeat_detections_core.py

@@ -297,10 +297,15 @@ def find_matches_in_directory(dirName, options, rowsByDirectory):
 
             # Is this detection too big to be suspicious?
             w, h = bbox[2], bbox[3]
+
+            if (w == 0 or h == 0):
+                # print('Illegal zero-size bounding box on image {}'.format(filename))
+                continue
+
             area = h * w
 
             # These are relative coordinates
-            assert area >= 0.0 and area <= 1.0
+            assert area >= 0.0 and area <= 1.0, 'Illegal bounding box area {}'.format(area)
 
             if area > options.maxSuspiciousDetectionSize:
                 # print('Ignoring very large detection with area {}'.format(area))
@@ -321,6 +326,7 @@ def find_matches_in_directory(dirName, options, rowsByDirectory):
                 try:
                     iou = ct_utils.get_iou(bbox, candidate.bbox)
                 except Exception as e:
+                    import pdb
                     print('Warning: IOU computation error on boxes ({},{},{},{}),({},{},{},{}): {}'.format(
                         bbox[0],bbox[1],bbox[2],bbox[3],
                         candidate.bbox[0],candidate.bbox[1],candidate.bbox[2],candidate.bbox[3], str(e)))

ct_utils.py

@@ -159,11 +159,11 @@ def get_iou(bb1, bb2):
     bb1 = convert_xywh_to_xyxy(bb1)
     bb2 = convert_xywh_to_xyxy(bb2)
 
-    assert bb1[0] < bb1[2]
-    assert bb1[1] < bb1[3]
+    assert bb1[0] < bb1[2], 'Malformed bounding box (x2 >= x1)'
+    assert bb1[1] < bb1[3], 'Malformed bounding box (y2 >= y1)'
 
-    assert bb2[0] < bb2[2]
-    assert bb2[1] < bb2[3]
+    assert bb2[0] < bb2[2], 'Malformed bounding box (x2 >= x1)'
+    assert bb2[1] < bb2[3], 'Malformed bounding box (y2 >= y1)'
 
     # Determine the coordinates of the intersection rectangle
     x_left = max(bb1[0], bb2[0])
@@ -186,6 +186,6 @@ def get_iou(bb1, bb2):
     # area and dividing it by the sum of prediction + ground-truth
     # areas - the intersection area.
     iou = intersection_area / float(bb1_area + bb2_area - intersection_area)
-    assert iou >= 0.0
-    assert iou <= 1.0
+    assert iou >= 0.0, 'Illegal IOU < 0'
+    assert iou <= 1.0, 'Illegal IOU > 1'
     return iou