--- a +++ b/tools/test.py @@ -0,0 +1,259 @@ +# Copyright (c) OpenMMLab. All rights reserved. +import argparse +import os +import os.path as osp +import shutil +import time +import warnings + +import mmcv +import torch +from mmcv.parallel import MMDataParallel, MMDistributedDataParallel +from mmcv.runner import (get_dist_info, init_dist, load_checkpoint, + wrap_fp16_model) +from mmcv.utils import DictAction + +from mmseg.apis import multi_gpu_test, single_gpu_test +from mmseg.datasets import build_dataloader, build_dataset +from mmseg.models import build_segmentor + + +def parse_args(): + parser = argparse.ArgumentParser( + description='mmseg test (and eval) a model') + parser.add_argument('config', help='test config file path') + parser.add_argument('checkpoint', help='checkpoint file') + parser.add_argument( + '--work-dir', + help=('if specified, the evaluation metric results will be dumped' + 'into the directory as json')) + parser.add_argument( + '--aug-test', action='store_true', help='Use Flip and Multi scale aug') + parser.add_argument('--out', help='output result file in pickle format') + parser.add_argument( + '--format-only', + action='store_true', + help='Format the output results without perform evaluation. It is' + 'useful when you want to format the result to a specific format and ' + 'submit it to the test server') + parser.add_argument( + '--eval', + type=str, + nargs='+', + help='evaluation metrics, which depends on the dataset, e.g., "mIoU"' + ' for generic datasets, and "cityscapes" for Cityscapes') + parser.add_argument('--show', action='store_true', help='show results') + parser.add_argument( + '--show-dir', help='directory where painted images will be saved') + parser.add_argument( + '--gpu-collect', + action='store_true', + help='whether to use gpu to collect results.') + parser.add_argument( + '--tmpdir', + help='tmp directory used for collecting results from multiple ' + 'workers, available when gpu_collect is not specified') + parser.add_argument( + '--options', + nargs='+', + action=DictAction, + help="--options is deprecated in favor of --cfg_options' and it will " + 'not be supported in version v0.22.0. Override some settings in the ' + 'used config, the key-value pair in xxx=yyy format will be merged ' + 'into config file. If the value to be overwritten is a list, it ' + 'should be like key="[a,b]" or key=a,b It also allows nested ' + 'list/tuple values, e.g. key="[(a,b),(c,d)]" Note that the quotation ' + 'marks are necessary and that no white space is allowed.') + parser.add_argument( + '--cfg-options', + nargs='+', + action=DictAction, + help='override some settings in the used config, the key-value pair ' + 'in xxx=yyy format will be merged into config file. If the value to ' + 'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' + 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' + 'Note that the quotation marks are necessary and that no white space ' + 'is allowed.') + parser.add_argument( + '--eval-options', + nargs='+', + action=DictAction, + help='custom options for evaluation') + parser.add_argument( + '--launcher', + choices=['none', 'pytorch', 'slurm', 'mpi'], + default='none', + help='job launcher') + parser.add_argument( + '--opacity', + type=float, + default=0.5, + help='Opacity of painted segmentation map. In (0, 1] range.') + parser.add_argument('--local_rank', type=int, default=0) + args = parser.parse_args() + if 'LOCAL_RANK' not in os.environ: + os.environ['LOCAL_RANK'] = str(args.local_rank) + + if args.options and args.cfg_options: + raise ValueError( + '--options and --cfg-options cannot be both ' + 'specified, --options is deprecated in favor of --cfg-options. ' + '--options will not be supported in version v0.22.0.') + if args.options: + warnings.warn('--options is deprecated in favor of --cfg-options. ' + '--options will not be supported in version v0.22.0.') + args.cfg_options = args.options + + return args + + +def main(): + args = parse_args() + + assert args.out or args.eval or args.format_only or args.show \ + or args.show_dir, \ + ('Please specify at least one operation (save/eval/format/show the ' + 'results / save the results) with the argument "--out", "--eval"' + ', "--format-only", "--show" or "--show-dir"') + + if args.eval and args.format_only: + raise ValueError('--eval and --format_only cannot be both specified') + + if args.out is not None and not args.out.endswith(('.pkl', '.pickle')): + raise ValueError('The output file must be a pkl file.') + + cfg = mmcv.Config.fromfile(args.config) + if args.cfg_options is not None: + cfg.merge_from_dict(args.cfg_options) + # set cudnn_benchmark + if cfg.get('cudnn_benchmark', False): + torch.backends.cudnn.benchmark = True + if args.aug_test: + # hard code index + cfg.data.test.pipeline[1].img_ratios = [ + 0.5, 0.75, 1.0, 1.25, 1.5, 1.75 + ] + cfg.data.test.pipeline[1].flip = True + cfg.model.pretrained = None + 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) + + rank, _ = get_dist_info() + # allows not to create + if args.work_dir is not None and rank == 0: + mmcv.mkdir_or_exist(osp.abspath(args.work_dir)) + timestamp = time.strftime('%Y%m%d_%H%M%S', time.localtime()) + json_file = osp.join(args.work_dir, f'eval_{timestamp}.json') + + # build the dataloader + # TODO: support multiple images per gpu (only minor changes are needed) + dataset = build_dataset(cfg.data.test) + data_loader = build_dataloader( + dataset, + samples_per_gpu=1, + workers_per_gpu=cfg.data.workers_per_gpu, + dist=distributed, + shuffle=False) + + # build the model and load checkpoint + cfg.model.train_cfg = None + model = build_segmentor(cfg.model, test_cfg=cfg.get('test_cfg')) + fp16_cfg = cfg.get('fp16', None) + if fp16_cfg is not None: + wrap_fp16_model(model) + checkpoint = load_checkpoint(model, args.checkpoint, map_location='cpu') + if 'CLASSES' in checkpoint.get('meta', {}): + model.CLASSES = checkpoint['meta']['CLASSES'] + else: + print('"CLASSES" not found in meta, use dataset.CLASSES instead') + model.CLASSES = dataset.CLASSES + if 'PALETTE' in checkpoint.get('meta', {}): + model.PALETTE = checkpoint['meta']['PALETTE'] + else: + print('"PALETTE" not found in meta, use dataset.PALETTE instead') + model.PALETTE = dataset.PALETTE + + # clean gpu memory when starting a new evaluation. + torch.cuda.empty_cache() + eval_kwargs = {} if args.eval_options is None else args.eval_options + + # Deprecated + efficient_test = eval_kwargs.get('efficient_test', False) + if efficient_test: + warnings.warn( + '``efficient_test=True`` does not have effect in tools/test.py, ' + 'the evaluation and format results are CPU memory efficient by ' + 'default') + + eval_on_format_results = ( + args.eval is not None and 'cityscapes' in args.eval) + if eval_on_format_results: + assert len(args.eval) == 1, 'eval on format results is not ' \ + 'applicable for metrics other than ' \ + 'cityscapes' + if args.format_only or eval_on_format_results: + if 'imgfile_prefix' in eval_kwargs: + tmpdir = eval_kwargs['imgfile_prefix'] + else: + tmpdir = '.format_cityscapes' + eval_kwargs.setdefault('imgfile_prefix', tmpdir) + mmcv.mkdir_or_exist(tmpdir) + else: + tmpdir = None + + if not distributed: + model = MMDataParallel(model, device_ids=[0]) + results = single_gpu_test( + model, + data_loader, + args.show, + args.show_dir, + False, + args.opacity, + pre_eval=args.eval is not None and not eval_on_format_results, + format_only=args.format_only or eval_on_format_results, + format_args=eval_kwargs) + else: + model = MMDistributedDataParallel( + model.cuda(), + device_ids=[torch.cuda.current_device()], + broadcast_buffers=False) + results = multi_gpu_test( + model, + data_loader, + args.tmpdir, + args.gpu_collect, + False, + pre_eval=args.eval is not None and not eval_on_format_results, + format_only=args.format_only or eval_on_format_results, + format_args=eval_kwargs) + + rank, _ = get_dist_info() + if rank == 0: + if args.out: + warnings.warn( + 'The behavior of ``args.out`` has been changed since MMSeg ' + 'v0.16, the pickled outputs could be seg map as type of ' + 'np.array, pre-eval results or file paths for ' + '``dataset.format_results()``.') + print(f'\nwriting results to {args.out}') + mmcv.dump(results, args.out) + if args.eval: + eval_kwargs.update(metric=args.eval) + metric = dataset.evaluate(results, **eval_kwargs) + metric_dict = dict(config=args.config, metric=metric) + if args.work_dir is not None and rank == 0: + mmcv.dump(metric_dict, json_file, indent=4) + if tmpdir is not None and eval_on_format_results: + # remove tmp dir when cityscapes evaluation + shutil.rmtree(tmpdir) + + +if __name__ == '__main__': + main()