update utils.create_pretrained()
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@@ -632,8 +632,8 @@ def strip_optimizer(f='weights/best.pt'): # from utils.utils import *; strip_op
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print('Optimizer stripped from %s' % f)
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def create_backbone(f='weights/best.pt', s='weights/backbone.pt'): # from utils.utils import *; create_backbone()
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# create backbone 's' from 'f'
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def create_pretrained(f='weights/best.pt', s='weights/pretrained.pt'): # from utils.utils import *; create_pretrained()
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# create pretrained checkpoint 's' from 'f' (create_pretrained(x, x) for x in glob.glob('./*.pt'))
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device = torch.device('cpu')
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x = torch.load(s, map_location=device)
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@@ -644,7 +644,7 @@ def create_backbone(f='weights/best.pt', s='weights/backbone.pt'): # from utils
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for p in x['model'].parameters():
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p.requires_grad = True
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torch.save(x, s)
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print('%s modified for backbone use and saved as %s' % (f, s))
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print('%s saved as pretrained checkpoint %s' % (f, s))
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def coco_class_count(path='../coco/labels/train2014/'):
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