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Fixed size crops #272

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markusnagel
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I added a transformer that performs a fixed size crop. It is similar to the already existing RandomFixedSizeCrop transformer. One key difference is that the user can specify the crop with a relative location instead of taking a random crop. This is useful for example for predicting on imagenet where often a center crop of the image is used or a center crop plus the 4 corner crops.

@vdumoulin
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@markusnagel Very sorry for the delay! I'll try to have a look at it by the end of the week.



class FixedSizeCrop(SourcewiseTransformer, ExpectsAxisLabels):
"""Crop images to a fixed window size.
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Sections in the docstring should have newlines.

@vdumoulin
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There seems to be quite a lot of overlap between FixedSizeCrop and RandomFixedSizeCrop. You could make FixedSizeCrop inherit from RandomFixedSizeCrop and factor cropping into _crop_batch and _crop_example methods which accept off_h and off_w arguments.

…_size_crops

Conflicts:
	fuel/transformers/image.py
	tests/transformers/test_image.py
@aukejw
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aukejw commented Mar 3, 2016

The FixedSizeCrop transformer will afaik not benefit from using window_batch_bchw. The same offset is used for all images in the batch, so you can simply use

return source[:, :, off_h:off_h + windowed_height, off_w:off_w + windowed_width]

rather than first constructing arrays offsets_h and offsets_w of the same length as the batch, then invoking window_batch_bchw.

Therefore, the FixedSizeCrop transformer currently does not call _crop_batch. I haven't tested whether it actually makes a difference in terms of speed, but it seems like overkill to use window_batch_bchw here - though I agree that it would be intuitive to abstract the cropping functionality.

@aukejw aukejw deleted the fixed_size_crops branch November 10, 2016 08:49
@aukejw aukejw restored the fixed_size_crops branch March 23, 2017 10:14
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4 participants