2bd4c84340a3c35b011026657a9ed30e380d0d75,tools/test.py,,main,#,62

Before Change

    else:
        model_args = cfg.model.copy()
        model_args.update(train_cfg=None, test_cfg=cfg.test_cfg)
        model_type = getattr(detectors, model_args.pop("type"))
        outputs = parallel_test(
            model_type,
            model_args,
            args.checkpoint,
            dataset,
            _data_func,
            range(args.gpus),
            workers_per_gpu=args.proc_per_gpu)

    if args.out:
        print("writing results to {}".format(args.out))
        mmcv.dump(outputs, args.out)

After Change

    cfg.data.test.test_mode = True

    // init distributed env first, since logger depends on the dist info.
    if args.launcher == "none":
        distributed = False
    else:
        distributed = True
        init_dist(args.launcher, **cfg.dist_params)

    // build the dataloader
    // TODO: support multiple images per gpu (only minor changes are needed)
    dataset = get_dataset(cfg.data.test)
    data_loader = build_dataloader(dataset,
                                   imgs_per_gpu=1,
                                   workers_per_gpu=cfg.data.workers_per_gpu,

Instances