我想以这种方式添加附加增强：
additional_aug=[zoom_crop(scale=(0.75,1.25), do_rand=False),
brightness(),
contrast()
]
tfms = get_transforms(do_flip=True,flip_vert=True,max_lighting=0.2, xtra_tfms=additional_aug)
data = (ImageList.from_df(df=df,path='./',cols='path')
.split_by_rand_pct(0.2)
.label_from_df(cols='diagnosis',label_cls=FloatList)
.transform(tfms,size=sz,resize_method=ResizeMethod.SQUISH,padding_mode='zeros')
.databunch(bs=bs,num_workers=4)
.normalize(imagenet_stats)
)
但是我收到错误：
--------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/opt/conda/lib/python3.6/site-packages/fastai/data_block.py in _check_kwargs(ds, tfms, **kwargs)
590 x = ds[0]
--> 591 try: x.apply_tfms(tfms, **kwargs)
592 except Exception as e:
/opt/conda/lib/python3.6/site-packages/fastai/vision/image.py in apply_tfms(self, tfms, do_resolve, xtra, size, resize_method, mult, padding_mode, mode, remove_out)
105 if resize_method <= 2 and size is not None: tfms = self._maybe_add_crop_pad(tfms)
--> 106 tfms = sorted(tfms, key=lambda o: o.tfm.order)
107 if do_resolve: _resolve_tfms(tfms)
/opt/conda/lib/python3.6/site-packages/fastai/vision/image.py in <lambda>(o)
105 if resize_method <= 2 and size is not None: tfms = self._maybe_add_crop_pad(tfms)
--> 106 tfms = sorted(tfms, key=lambda o: o.tfm.order)
107 if do_resolve: _resolve_tfms(tfms)
AttributeError: 'list' object has no attribute 'tfm'
During handling of the above exception, another exception occurred:
Exception Traceback (most recent call last)
<ipython-input-27-3daf86c69a96> in <module>
2 .split_by_rand_pct(0.2)
3 .label_from_df(cols='diagnosis',label_cls=FloatList)
----> 4 .transform(tfms,size=sz,resize_method=ResizeMethod.SQUISH,padding_mode='zeros')
5 .databunch(bs=bs,num_workers=4)
6 .normalize(imagenet_stats)
/opt/conda/lib/python3.6/site-packages/fastai/data_block.py in transform(self, tfms, **kwargs)
500 if not tfms: tfms=(None,None)
501 assert is_listy(tfms) and len(tfms) == 2, "Please pass a list of two lists of transforms (train and valid)."
--> 502 self.train.transform(tfms[0], **kwargs)
503 self.valid.transform(tfms[1], **kwargs)
504 if self.test: self.test.transform(tfms[1], **kwargs)
/opt/conda/lib/python3.6/site-packages/fastai/data_block.py in transform(self, tfms, tfm_y, **kwargs)
719 def transform(self, tfms:TfmList, tfm_y:bool=None, **kwargs):
720 "Set the `tfms` and `tfm_y` value to be applied to the inputs and targets."
--> 721 _check_kwargs(self.x, tfms, **kwargs)
722 if tfm_y is None: tfm_y = self.tfm_y
723 tfms_y = None if tfms is None else list(filter(lambda t: getattr(t, 'use_on_y', True), listify(tfms)))
/opt/conda/lib/python3.6/site-packages/fastai/data_block.py in _check_kwargs(ds, tfms, **kwargs)
591 try: x.apply_tfms(tfms, **kwargs)
592 except Exception as e:
--> 593 raise Exception(f"It's not possible to apply those transforms to your dataset:n {e}")
594
595 class LabelList(Dataset):
Exception: It's not possible to apply those transforms to your dataset:
'list' object has no attribute 'tfm'
根据文档xtra_tfms：Optional[Collection[Transform]]=None( →Collection[Transform]
如何让它工作？
我遇到了这个问题，解决方案非常简单。只需在列表括起来的单独列表中调用要应用的每个转换函数，并将其传递到get_transforms函数的xtra_tfms参数中。(它甚至可以是元组的元组或任何集合(
additional_aug=[[zoom_crop(scale=(0.75,1.25), do_rand=False)],
[brightness()],
[contrast()]]
tfms = get_transforms(do_flip=True,
flip_vert=True,
max_lighting=0.2,
xtra_tfms=additional_aug)
希望这能解决您的问题。