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import os |
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os.system("pip uninstall -y mmcv-full") |
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os.system("mim install 'mmengine>=0.6.0'") |
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os.system("mim install 'mmcv-lite==2.0.1'") |
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os.system("mim install 'mmdet>=3.0.0,<4.0.0'") |
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os.system("mim install 'mmyolo'") |
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os.system("pip install -e .") |
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os.system("python tools/demo.py configs/pretrain/yolo_world_l_t2i_bn_2e-4_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py yolow-v8_l_clipv2_frozen_t2iv2_bn_o365_goldg_pretrain.pth") |
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import argparse |
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import os.path as osp |
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from mmengine.config import Config, DictAction |
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from mmengine.runner import Runner |
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from mmengine.dataset import Compose |
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from mmyolo.registry import RUNNERS |
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from tools.demo import demo |
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def parse_args(): |
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parser = argparse.ArgumentParser( |
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description='YOLO-World Demo') |
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parser.add_argument('--config', default='configs/pretrain/yolo_world_l_t2i_bn_2e-4_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py') |
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parser.add_argument('--checkpoint', default='yolow-v8_l_clipv2_frozen_t2iv2_bn_o365_goldg_pretrain.pth') |
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parser.add_argument( |
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'--work-dir', |
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help='the directory to save the file containing evaluation metrics') |
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parser.add_argument( |
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'--cfg-options', |
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nargs='+', |
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action=DictAction, |
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help='override some settings in the used config, the key-value pair ' |
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'in xxx=yyy format will be merged into config file. If the value to ' |
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'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' |
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'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' |
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'Note that the quotation marks are necessary and that no white space ' |
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'is allowed.') |
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args = parser.parse_args() |
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return args |
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if __name__ == '__main__': |
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args = parse_args() |
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cfg = Config.fromfile(args.config) |
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if args.cfg_options is not None: |
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cfg.merge_from_dict(args.cfg_options) |
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if args.work_dir is not None: |
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cfg.work_dir = args.work_dir |
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elif cfg.get('work_dir', None) is None: |
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cfg.work_dir = osp.join('./work_dirs', |
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osp.splitext(osp.basename(args.config))[0]) |
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cfg.load_from = args.checkpoint |
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if 'runner_type' not in cfg: |
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runner = Runner.from_cfg(cfg) |
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else: |
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runner = RUNNERS.build(cfg) |
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runner.call_hook('before_run') |
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runner.load_or_resume() |
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pipeline = cfg.test_dataloader.dataset.pipeline |
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runner.pipeline = Compose(pipeline) |
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runner.model.eval() |
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demo(runner, args) |
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