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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
from collections import OrderedDict
import torch
convert_dict_s = {
# backbone
'model.0': 'backbone.stem',
'model.1': 'backbone.stage1.0',
'model.2': 'backbone.stage1.1',
'model.3': 'backbone.stage2.0',
'model.4': 'backbone.stage2.1',
'model.5': 'backbone.stage3.0',
'model.6': 'backbone.stage3.1',
'model.7': 'backbone.stage4.0',
'model.8': 'backbone.stage4.1',
'model.9': 'backbone.stage4.2',
# neck
'model.12': 'neck.top_down_layers.0',
'model.15': 'neck.top_down_layers.1',
'model.16': 'neck.downsample_layers.0',
'model.18': 'neck.bottom_up_layers.0',
'model.19': 'neck.downsample_layers.1',
'model.21': 'neck.bottom_up_layers.1',
# Detector
'model.22': 'bbox_head.head_module',
}
def convert(src, dst):
"""Convert keys in pretrained YOLOv8 models to mmyolo style."""
convert_dict = convert_dict_s
try:
yolov8_model = torch.load(src)['model']
blobs = yolov8_model.state_dict()
except ModuleNotFoundError:
raise RuntimeError(
'This script must be placed under the ultralytics repo,'
' because loading the official pretrained model need'
' `model.py` to build model.'
'Also need to install hydra-core>=1.2.0 and thop>=0.1.1')
state_dict = OrderedDict()
for key, weight in blobs.items():
num, module = key.split('.')[1:3]
prefix = f'model.{num}'
new_key = key.replace(prefix, convert_dict[prefix])
if '.m.' in new_key:
new_key = new_key.replace('.m.', '.blocks.')
new_key = new_key.replace('.cv', '.conv')
elif 'bbox_head.head_module.proto.cv' in new_key:
new_key = new_key.replace(
'bbox_head.head_module.proto.cv',
'bbox_head.head_module.proto_preds.conv')
elif 'bbox_head.head_module.proto' in new_key:
new_key = new_key.replace('bbox_head.head_module.proto',
'bbox_head.head_module.proto_preds')
elif 'bbox_head.head_module.cv4.' in new_key:
new_key = new_key.replace(
'bbox_head.head_module.cv4',
'bbox_head.head_module.mask_coeff_preds')
new_key = new_key.replace('.2.weight', '.2.conv.weight')
new_key = new_key.replace('.2.bias', '.2.conv.bias')
elif 'bbox_head.head_module' in new_key:
new_key = new_key.replace('.cv2', '.reg_preds')
new_key = new_key.replace('.cv3', '.cls_preds')
elif 'backbone.stage4.2' in new_key:
new_key = new_key.replace('.cv', '.conv')
else:
new_key = new_key.replace('.cv1', '.main_conv')
new_key = new_key.replace('.cv2', '.final_conv')
if 'bbox_head.head_module.dfl.conv.weight' == new_key:
print('Drop "bbox_head.head_module.dfl.conv.weight", '
'because it is useless')
continue
state_dict[new_key] = weight
print(f'Convert {key} to {new_key}')
# save checkpoint
checkpoint = dict()
checkpoint['state_dict'] = state_dict
torch.save(checkpoint, dst)
# Note: This script must be placed under the ultralytics repo to run.
def main():
parser = argparse.ArgumentParser(description='Convert model keys')
parser.add_argument(
'--src', default='yolov8s.pt', help='src YOLOv8 model path')
parser.add_argument('--dst', default='mmyolov8s.pth', help='save path')
args = parser.parse_args()
convert(args.src, args.dst)
if __name__ == '__main__':
main()
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