def test_CaffePostprocessing(pixel, caffe_mean, caffe_std):
processing = enc.CaffePostprocessing()
expected = pixel
input = pixel.sub(caffe_mean).div(caffe_std).mul(255).flip(1)
actual = processing(input)
ptu.assert_allclose(actual, expected, rtol=1e-6)
def postprocessor(impl_params: bool = True) -> nn.Module:
r"""Postprocessor from :cite:`JAL2016`.
Args:
impl_params: If ``True``, the input is postprocessed from models trained with
the Caffe framework. If ``False``, the postprocessor performs the identity
operation.
.. seealso::
- :class:`pystiche.enc.CaffePostprocessing`
"""
# https://github.com/pmeier/fast-neural-style/blob/813c83441953ead2adb3f65f4cc2d5599d735fa7/fast_neural_style/preprocess.lua#L66-L71
# https://github.com/pmeier/fast-neural-style/blob/813c83441953ead2adb3f65f4cc2d5599d735fa7/fast_neural_style.lua#L89
return enc.CaffePostprocessing() if impl_params else Identity()
def postprocessor() -> nn.Module:
return enc.CaffePostprocessing()
def postprocessor() -> enc.CaffePostprocessing:
r"""Postprocessor from :cite:`LW2016`."""
return enc.CaffePostprocessing()
def postprocessor() -> enc.CaffePostprocessing:
return enc.CaffePostprocessing()