def test_can_find_bbox_with_wrong_label(self):
detections = 3
class_count = 2
item1 = DatasetItem(id=1,
annotations=[
Bbox(i * 10, 10, 10, 10, label=i)
for i in range(detections)
])
item2 = DatasetItem(id=2,
annotations=[
Bbox(i * 10,
10,
10,
10,
label=(i + 1) % class_count)
for i in range(detections)
])
iou_thresh = 0.5
comp = DistanceComparator(iou_threshold=iou_thresh)
result = comp.match_boxes(item1, item2)
matches, mispred, a_greater, b_greater = result
self.assertEqual(len(item1.annotations), len(mispred))
self.assertEqual(0, len(a_greater))
self.assertEqual(0, len(b_greater))
self.assertEqual(0, len(matches))
for a_bbox, b_bbox in mispred:
self.assertLess(iou_thresh, a_bbox.iou(b_bbox))
self.assertEqual((a_bbox.label + 1) % class_count, b_bbox.label)
def test_can_find_missing_boxes(self):
detections = 3
class_count = 2
item1 = DatasetItem(id=1,
annotations=[
Bbox(i * 10, 10, 10, 10, label=i)
for i in range(detections) if i % 2 == 0
])
item2 = DatasetItem(id=2,
annotations=[
Bbox(i * 10,
10,
10,
10,
label=(i + 1) % class_count)
for i in range(detections) if i % 2 == 1
])
iou_thresh = 0.5
comp = DistanceComparator(iou_threshold=iou_thresh)
result = comp.match_boxes(item1, item2)
matches, mispred, a_greater, b_greater = result
self.assertEqual(0, len(mispred))
self.assertEqual(len(item1.annotations), len(a_greater))
self.assertEqual(len(item2.annotations), len(b_greater))
self.assertEqual(0, len(matches))
def test_no_bbox_diff_with_same_item(self):
detections = 3
anns = [Bbox(i * 10, 10, 10, 10, label=i) for i in range(detections)]
item = DatasetItem(id=0, annotations=anns)
iou_thresh = 0.5
comp = DistanceComparator(iou_threshold=iou_thresh)
result = comp.match_boxes(item, item)
matches, mispred, a_greater, b_greater = result
self.assertEqual(0, len(mispred))
self.assertEqual(0, len(a_greater))
self.assertEqual(0, len(b_greater))
self.assertEqual(len(item.annotations), len(matches))
for a_bbox, b_bbox in matches:
self.assertLess(iou_thresh, a_bbox.iou(b_bbox))
self.assertEqual(a_bbox.label, b_bbox.label)