mirror of https://github.com/JDAI-CV/fast-reid.git
87 lines
2.1 KiB
Python
87 lines
2.1 KiB
Python
# encoding: utf-8
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"""
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@author: sherlock
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@contact: sherlockliao01@gmail.com
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"""
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import logging
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import sys
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sys.path.append('.')
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from fastreid.config import get_cfg
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from fastreid.engine import default_argument_parser, default_setup, launch
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from fastreid.utils.checkpoint import Checkpointer
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from fastreid.engine import DefaultTrainer
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from fastreid.data import build_reid_train_loader
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from naic import *
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class Trainer(DefaultTrainer):
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@classmethod
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def build_train_loader(cls, cfg):
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logger = logging.getLogger("fastreid.naic20")
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logger.info("Prepare NAIC20 competition trainset")
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return build_reid_train_loader(cfg, rm_lt=cfg.DATASETS.RM_LT)
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class Committer(DefaultTrainer):
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@classmethod
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def build_evaluator(cls, cfg, dataset_name, output_dir=None):
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data_loader, num_query = cls.build_test_loader(cfg, dataset_name)
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return data_loader, NaicEvaluator(cfg, num_query, output_dir)
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def setup(args):
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"""
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Create configs and perform basic setups.
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"""
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cfg = get_cfg()
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add_naic_config(cfg)
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cfg.merge_from_file(args.config_file)
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cfg.merge_from_list(args.opts)
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cfg.freeze()
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default_setup(cfg, args)
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return cfg
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def main(args):
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cfg = setup(args)
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if args.eval_only:
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cfg.defrost()
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cfg.MODEL.BACKBONE.PRETRAIN = False
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model = Trainer.build_model(cfg)
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Checkpointer(model, save_dir=cfg.OUTPUT_DIR).load(cfg.MODEL.WEIGHTS) # load trained model
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if args.commit:
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res = Committer.test(cfg, model)
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else:
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res = Trainer.test(cfg, model)
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return res
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trainer = Trainer(cfg)
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trainer.resume_or_load(resume=args.resume)
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return trainer.train()
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if __name__ == "__main__":
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parser = default_argument_parser()
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parser.add_argument("--commit", action="store_true", help="submission testing results")
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args = parser.parse_args()
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print("Command Line Args:", args)
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launch(
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main,
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args.num_gpus,
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num_machines=args.num_machines,
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machine_rank=args.machine_rank,
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dist_url=args.dist_url,
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args=(args,),
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)
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