fast-reid/projects/FastClas/train_net.py

74 lines
1.7 KiB
Python

#!/usr/bin/env python
# encoding: utf-8
"""
@author: sherlock
@contact: sherlockliao01@gmail.com
"""
import json
import logging
import os
import sys
sys.path.append('.')
from fastreid.config import get_cfg
from fastreid.engine import default_argument_parser, default_setup, launch
from fastreid.utils.checkpoint import Checkpointer, PathManager
from fastclas import *
def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
default_setup(cfg, args)
return cfg
def main(args):
cfg = setup(args)
if args.eval_only:
cfg.defrost()
cfg.MODEL.BACKBONE.PRETRAIN = False
model = ClasTrainer.build_model(cfg)
Checkpointer(model).load(cfg.MODEL.WEIGHTS) # load trained model
try:
output_dir = os.path.dirname(cfg.MODEL.WEIGHTS)
path = os.path.join(output_dir, "idx2class.json")
with PathManager.open(path, 'r') as f:
idx2class = json.load(f)
ClasTrainer.idx2class = idx2class
except:
logger = logging.getLogger("fastreid.fastclas")
logger.info(f"Cannot find idx2class dict in {os.path.dirname(cfg.MODEL.WEIGHTS)}")
res = ClasTrainer.test(cfg, model)
return res
trainer = ClasTrainer(cfg)
trainer.resume_or_load(resume=args.resume)
return trainer.train()
if __name__ == "__main__":
args = default_argument_parser().parse_args()
print("Command Line Args:", args)
launch(
main,
args.num_gpus,
num_machines=args.num_machines,
machine_rank=args.machine_rank,
dist_url=args.dist_url,
args=(args,),
)