python - 如何在fastai中向get_transform添加额外的变换？

Question

我想通过这种方式添加额外的增强功能:

 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:可选 [ 集合 [ Transform ]]= 无 ) →  集合 [ Transform ]

如何让它发挥作用？

Answer 1

我也遇到过这个问题，解决方法也很简单。只需调用要在列表包围的单独列表中应用的每个变换函数，并将其传递到 get_transforms 函数的 xtra_tfms 参数中即可。 (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。