Can I define more complex transformations of the dataset after the standard ones in

```
tfms = tfms_from_model(resnet34, sz, aug_tfms=transforms_side_on, max_zoom=1.1)
data = ImageClassifierData.from_paths(PATH, tfms=tfms)
```

I would like to do Fourier transform of already rotated, cropped and zoomed image. May be the file https://github.com/fastai/fastai/blob/master/fastai/transforms.py should be modified somehow.

```
def transf(image):
A = np.exp(image)
A = np.fft.fft2(A)
return np.log(np.abs(A))
```