diff --git a/timm/models/efficientvit_mit.py b/timm/models/efficientvit_mit.py index b464fc88..1960d3d2 100644 --- a/timm/models/efficientvit_mit.py +++ b/timm/models/efficientvit_mit.py @@ -947,31 +947,56 @@ default_cfgs = generate_default_cfgs({ input_size=(3, 288, 288), pool_size=(9, 9), crop_pct=1.0, ), 'efficientvit_l1.r224_in1k': _cfg( - # hf_hub_id='timm/', + hf_hub_id='timm/', + crop_pct=1.0, ), 'efficientvit_l2.r224_in1k': _cfg( - # hf_hub_id='timm/', + hf_hub_id='timm/', + crop_pct=1.0, + ), + 'efficientvit_l2.r256_in1k': _cfg( + hf_hub_id='timm/', + input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=1.0, + ), + 'efficientvit_l2.r288_in1k': _cfg( + hf_hub_id='timm/', + input_size=(3, 288, 288), pool_size=(9, 9), crop_pct=1.0, ), 'efficientvit_l2.r384_in1k': _cfg( - # hf_hub_id='timm/', + hf_hub_id='timm/', input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0, ), 'efficientvit_l3.r224_in1k': _cfg( - # hf_hub_id='timm/', + hf_hub_id='timm/', + crop_pct=1.0, + ), + 'efficientvit_l3.r256_in1k': _cfg( + hf_hub_id='timm/', + input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=1.0, + ), + 'efficientvit_l3.r320_in1k': _cfg( + hf_hub_id='timm/', + input_size=(3, 320, 320), pool_size=(10, 10), crop_pct=1.0, ), 'efficientvit_l3.r384_in1k': _cfg( - # hf_hub_id='timm/', + hf_hub_id='timm/', input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0, ), - 'efficientvit_l0_sam.sam': _cfg( - # hf_hub_id='timm/', - ), - 'efficientvit_l1_sam.sam': _cfg( - # hf_hub_id='timm/', - ), - 'efficientvit_l2_sam.sam': _cfg( - # hf_hub_id='timm/', - ), + # 'efficientvit_l0_sam.sam': _cfg( + # # hf_hub_id='timm/', + # input_size=(3, 512, 512), crop_pct=1.0, + # num_classes=0, + # ), + # 'efficientvit_l1_sam.sam': _cfg( + # # hf_hub_id='timm/', + # input_size=(3, 512, 512), crop_pct=1.0, + # num_classes=0, + # ), + # 'efficientvit_l2_sam.sam': _cfg( + # # hf_hub_id='timm/',f + # input_size=(3, 512, 512), crop_pct=1.0, + # num_classes=0, + # ), }) @@ -1048,22 +1073,26 @@ def efficientvit_l3(pretrained=False, **kwargs): return _create_efficientvit_large('efficientvit_l3', pretrained=pretrained, **dict(model_args, **kwargs)) -@register_model -def efficientvit_l0_sam(pretrained=False, **kwargs): - model_args = dict( - widths=(32, 64, 128, 256, 512), depths=(1, 1, 1, 4, 4), head_dim=32, num_classes=0, norm_eps=1e-6) # only backbone for segment-anything-model weights - return _create_efficientvit_large('efficientvit_l0_sam', pretrained=pretrained, **dict(model_args, **kwargs)) - - -@register_model -def efficientvit_l1_sam(pretrained=False, **kwargs): - model_args = dict( - widths=(32, 64, 128, 256, 512), depths=(1, 1, 1, 6, 6), head_dim=32, num_classes=0, norm_eps=1e-6) # only backbone for segment-anything-model weights - return _create_efficientvit_large('efficientvit_l1_sam', pretrained=pretrained, **dict(model_args, **kwargs)) - - -@register_model -def efficientvit_l2_sam(pretrained=False, **kwargs): - model_args = dict( - widths=(32, 64, 128, 256, 512), depths=(1, 2, 2, 8, 8), head_dim=32, num_classes=0, norm_eps=1e-6) # only backbone for segment-anything-model weights - return _create_efficientvit_large('efficientvit_l2_sam', pretrained=pretrained, **dict(model_args, **kwargs)) +# FIXME will wait for v2 SAM models which are pending +# @register_model +# def efficientvit_l0_sam(pretrained=False, **kwargs): +# # only backbone for segment-anything-model weights +# model_args = dict( +# widths=(32, 64, 128, 256, 512), depths=(1, 1, 1, 4, 4), head_dim=32, num_classes=0, norm_eps=1e-6) +# return _create_efficientvit_large('efficientvit_l0_sam', pretrained=pretrained, **dict(model_args, **kwargs)) +# +# +# @register_model +# def efficientvit_l1_sam(pretrained=False, **kwargs): +# # only backbone for segment-anything-model weights +# model_args = dict( +# widths=(32, 64, 128, 256, 512), depths=(1, 1, 1, 6, 6), head_dim=32, num_classes=0, norm_eps=1e-6) +# return _create_efficientvit_large('efficientvit_l1_sam', pretrained=pretrained, **dict(model_args, **kwargs)) +# +# +# @register_model +# def efficientvit_l2_sam(pretrained=False, **kwargs): +# # only backbone for segment-anything-model weights +# model_args = dict( +# widths=(32, 64, 128, 256, 512), depths=(1, 2, 2, 8, 8), head_dim=32, num_classes=0, norm_eps=1e-6) +# return _create_efficientvit_large('efficientvit_l2_sam', pretrained=pretrained, **dict(model_args, **kwargs))