Method test_with_TTA

projects/SparseRCNN/train_net.py:104–117

(cls, cfg, model)

    @classmethod
    def test_with_TTA(cls, cfg, model):
        logger = logging.getLogger("detectron2.trainer")
        # Only support Sparse R-CNN models.
        logger.info("Running inference with test-time augmentation ...")
        model = SparseRCNNWithTTA(cfg, model)
        evaluators = [
            cls.build_evaluator(
                cfg, name, output_folder=os.path.join(cfg.OUTPUT_DIR, "inference_TTA")
            )
            for name in cfg.DATASETS.TEST
        ]
        res = cls.test(cfg, model, evaluators)
        res = OrderedDict({k + "_TTA": v for k, v in res.items()})
        return res

def setup(args):
    """