mirror of
https://github.com/open-mmlab/mmyolo.git
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4b996f10a5
* init * add cfg * update align * update * fix regularize box * fix comment * update config * remove ckpt * update * make mmrotate optional * fix doc * add mmrotate req * support large_demo with rbbox * add ut * update * add doc v01 * update doc * fix doc * update * update * update readme * update comments * fix * fix doc * fix doc * fix * update * update * fix large * update doc * update readme * fix config * fix configs * inprove * update doc * update assigner * update ut * remove rdsl assigner * rename aug config * speedup ut * add comment * fix data root * remove doc * remove empty folder * add docs * rename configs * fix readme * fix readme * fix configs * revert * fix name * fix table * fix doc link * fix doc link * update * update * update * Refactor dota splits * add shapely * fix typo * fix ci * change * fix type * uppdata link * uppdata link * add some comment * update --------- Co-authored-by: huanghaian <huanghaian@sensetime.com>
62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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from collections import OrderedDict
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import torch
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def convert(src, dst):
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"""Convert keys in pretrained RTMDet models to MMYOLO style."""
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blobs = torch.load(src)['state_dict']
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state_dict = OrderedDict()
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for key, weight in blobs.items():
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if 'neck.reduce_layers.0' in key:
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new_key = key.replace('.0', '.2')
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state_dict[new_key] = weight
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elif 'neck.reduce_layers.1' in key:
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new_key = key.replace('reduce_layers.1', 'top_down_layers.0.1')
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state_dict[new_key] = weight
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elif 'neck.top_down_blocks.0' in key:
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new_key = key.replace('down_blocks', 'down_layers.0')
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state_dict[new_key] = weight
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elif 'neck.top_down_blocks.1' in key:
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new_key = key.replace('down_blocks', 'down_layers')
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state_dict[new_key] = weight
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elif 'downsamples' in key:
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new_key = key.replace('downsamples', 'downsample_layers')
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state_dict[new_key] = weight
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elif 'bottom_up_blocks' in key:
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new_key = key.replace('bottom_up_blocks', 'bottom_up_layers')
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state_dict[new_key] = weight
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elif 'out_convs' in key:
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new_key = key.replace('out_convs', 'out_layers')
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state_dict[new_key] = weight
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elif 'bbox_head' in key:
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new_key = key.replace('bbox_head', 'bbox_head.head_module')
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state_dict[new_key] = weight
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elif 'data_preprocessor' in key:
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continue
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else:
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new_key = key
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state_dict[new_key] = weight
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print(f'Convert {key} to {new_key}')
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# save checkpoint
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checkpoint = dict()
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checkpoint['state_dict'] = state_dict
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checkpoint['meta'] = blobs.get('meta')
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torch.save(checkpoint, dst)
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def main():
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parser = argparse.ArgumentParser(description='Convert model keys')
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parser.add_argument('src', help='src rtm model path')
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parser.add_argument('dst', help='save path')
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args = parser.parse_args()
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convert(args.src, args.dst)
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if __name__ == '__main__':
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main()
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