mirror of https://github.com/JDAI-CV/fast-reid.git
91 lines
2.3 KiB
Python
91 lines
2.3 KiB
Python
# encoding: utf-8
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"""
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@author: xingyu liao
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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 DefaultTrainer
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from fastreid.modeling import build_model
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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 fastattr import *
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class Trainer(DefaultTrainer):
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def build_model(self, cfg):
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"""
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Returns:
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torch.nn.Module:
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It now calls :func:`fastreid.modeling.build_model`.
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Overwrite it if you'd like a different model.
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"""
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model = build_model(cfg, sample_weights=self.sample_weights)
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logger = logging.getLogger("fastreid.attr_model")
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logger.info("Model:\n{}".format(model))
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return model
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def build_train_loader(self, cfg):
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data_loader = build_attr_train_loader(cfg)
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self.sample_weights = data_loader.dataset.sample_weights
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return data_loader
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@classmethod
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def build_test_loader(cls, cfg, dataset_name):
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return build_attr_test_loader(cfg, dataset_name)
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@classmethod
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def build_evaluator(cls, cfg, dataset_name, output_folder=None):
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data_loader = cls.build_test_loader(cfg, dataset_name)
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return data_loader, AttrEvaluator(cfg, output_folder)
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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_attr_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).load(cfg.MODEL.WEIGHTS) # load trained model
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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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args = default_argument_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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