Chengfang Lu
7c43b44c57
Huaxu Sentinel Active Safety Platform with embedded algorithm code, Docker Compose setup, and vendored dataset scaffolds for clone-and-run. Co-authored-by: Cursor <cursoragent@cursor.com>
65 lines
2.7 KiB
Python
65 lines
2.7 KiB
Python
import torch
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import argparse
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try:
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from utils.common import warnings
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except ImportError:
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import warnings
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from utils.args import parse_arg_cfg, read_config, map_states, add_shortcuts, cmd_dict
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from utils.runners import SegTrainer, SegTester
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if __name__ == '__main__':
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# Settings (user input > config > argparse defaults)
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parser = argparse.ArgumentParser(description='PytorchAutoDrive Semantic Segmentation', conflict_handler='resolve')
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add_shortcuts(parser)
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# Required args
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parser.add_argument('--config', type=str, help='Path to config file', required=True)
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group = parser.add_mutually_exclusive_group(required=True)
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group.add_argument('--train', action='store_true')
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group.add_argument('--val', action='store_true') # There is no test labels available for these datasets
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group.add_argument('--state', type=int,
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help='[Deprecated] validation set testing(1)/training(0)')
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# Optional args/to overwrite configs
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group2 = parser.add_mutually_exclusive_group()
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group2.add_argument('--continue-from', type=str,
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help='[Deprecated] Continue training from a previous checkpoint')
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group2.add_argument('--checkpoint', type=str,
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help='Continue/Load from a previous checkpoint')
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# Optional args/to overwrite configs
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group2 = parser.add_mutually_exclusive_group()
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group2.add_argument('--continue-from', type=str,
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help='[Deprecated] Continue training from a previous checkpoint')
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group2.add_argument('--checkpoint', type=str,
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help='Continue/Load from a previous checkpoint')
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parser.add_argument('--mixed-precision', action='store_true',
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help='Enable mixed precision training')
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parser.add_argument('--cfg-options', type=cmd_dict,
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help='Override config options with \"x1=y1 x2=y2 xn=yn\"')
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states = ['train', 'val']
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retain_args = ['state', 'mixed_precision']
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args = parser.parse_args()
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if args.state is not None:
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warnings.warn('--state={} is deprecated, it is recommended to specify with --{}'.format(
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args.state, states[args.state]))
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args.state = map_states(args, states)
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if args.mixed_precision and torch.__version__ < '1.6.0':
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warnings.warn('PyTorch version too low, mixed precision training is not available.')
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# Parse configs and execute runner
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cfg = read_config(args.config)
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cfg_runner_key = 'train' if args.state == 0 else 'test'
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Runner = SegTrainer if args.state == 0 else SegTester
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args, cfg = parse_arg_cfg(args, cfg)
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for k in retain_args:
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cfg[cfg_runner_key][k] = vars(args)[k]
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runner = Runner(cfg=cfg)
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runner.run()
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runner.clean()
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