mirror of https://github.com/JDAI-CV/fast-reid.git
74 lines
1.7 KiB
Python
74 lines
1.7 KiB
Python
#!/usr/bin/env python
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# 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 json
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import logging
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import os
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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, PathManager
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from fastclas import *
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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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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 = ClasTrainer.build_model(cfg)
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Checkpointer(model).load(cfg.MODEL.WEIGHTS) # load trained model
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try:
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output_dir = os.path.dirname(cfg.MODEL.WEIGHTS)
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path = os.path.join(output_dir, "idx2class.json")
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with PathManager.open(path, 'r') as f:
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idx2class = json.load(f)
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ClasTrainer.idx2class = idx2class
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except:
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logger = logging.getLogger("fastreid.fastclas")
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logger.info(f"Cannot find idx2class dict in {os.path.dirname(cfg.MODEL.WEIGHTS)}")
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res = ClasTrainer.test(cfg, model)
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return res
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trainer = ClasTrainer(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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