def test_not_gt_boxes_for_box_matching(self):
gt = make_representation(["0 0 0 5 5"], is_ground_truth=True)
pred = make_representation(["1 0 0 5 5"], score=1)
metric = _test_metric_wrapper(Recall, multi_class_dataset_without_background())
assert 0 == metric(gt, pred)[0]
assert metric.meta.get('names') == ['cat']
def test_on_dataset_without_background(self):
gt = make_representation(["0 0 0 5 5; 1 10 10 20 20", "1 0 0 5 5"], is_ground_truth=True)
pred = make_representation(["0 0 0 5 5; 1 10 10 20 20", "1 0 0 5 5"], score=1)
with pytest.warns(None) as warnings:
_test_metric_wrapper(Recall, multi_class_dataset_without_background())(gt, pred)
assert len(warnings) == 0
def test_detection_on_dataset_without_background(self):
gt = make_representation(["0 0 0 5 5; 1 10 10 20 20", "1 0 0 5 5"], is_ground_truth=True)
pred = make_representation(["0 0 0 5 5; 1 10 10 20 20", "1 0 0 5 5"], score=1)
with pytest.warns(None) as warnings:
map_ = _test_metric_wrapper(DetectionMAP, multi_class_dataset_without_background())(gt, pred)
mean = np.mean(map_)
assert 1.0 == mean
assert len(warnings) == 0