def test_match_coco_at_150(self):
matcher = MatchEngineEuclideanDistance(150, 'coco')
assert np.all(
matcher.match(detections, gt) == np.array(
[[0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0], [1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]))
def test_match_xview_at_200(self):
matcher = MatchEngineEuclideanDistance(200, 'xview')
assert np.all(
matcher.match(detections, gt) == np.array(
[[0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0], [1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0]]))
def test_similarity(self, th):
matcher = MatchEngineEuclideanDistance(th, 'coco')
ref_iou = naive_compute_threshold_distance_similarity_matrix(
sort_detection_by_confidence(detections), gt, th)
iou = matcher.compute_similarity_matrix(detections, gt)
print(iou)
print(ref_iou)
assert np.all(iou[np.logical_not(np.isinf(iou))] == ref_iou[
np.logical_not(np.isinf(iou))])
