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Update default crop_pct for byoanet

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pull/880/head
Ross Wightman 3 years ago
parent cc9bedf373
commit da0d39bedd
1 changed files with 3 additions and 3 deletions
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6
timm/models/byoanet.py
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@ -23,7 +23,7 @@ __all__ = []
def _cfg(url='', **kwargs): def _cfg(url='', **kwargs):
return { return {
'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7), 'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
'crop_pct': 0.875, 'interpolation': 'bicubic', 'crop_pct': 0.95, 'interpolation': 'bicubic',
'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD, 'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
'first_conv': 'stem.conv1.conv', 'classifier': 'head.fc', 'first_conv': 'stem.conv1.conv', 'classifier': 'head.fc',
'fixed_input_size': False, 'min_input_size': (3, 224, 224), 'fixed_input_size': False, 'min_input_size': (3, 224, 224),
@ -35,7 +35,7 @@ default_cfgs = {
# GPU-Efficient (ResNet) weights # GPU-Efficient (ResNet) weights
'botnet26t_256': _cfg( 'botnet26t_256': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/botnet26t_c1_256-167a0e9f.pth', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/botnet26t_c1_256-167a0e9f.pth',
fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=0.95), fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
'botnet50ts_256': _cfg( 'botnet50ts_256': _cfg(
url='', url='',
fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)), fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
@ -59,7 +59,7 @@ default_cfgs = {
'lambda_resnet26t': _cfg( 'lambda_resnet26t': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26t_a2h_256-25ded63d.pth', url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26t_a2h_256-25ded63d.pth',
min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=0.95), min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)),
'lambda_resnet50ts': _cfg( 'lambda_resnet50ts': _cfg(
url='', url='',
min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)), min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)),

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