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))])