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seanbell / intrinsic

Code for Bell et al, "Intrinsic Images in the Wild", SIGGRAPH 2014.
MIT License
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results different .. reflectance much lighter than the one from the paper #3

Open lulu1315 opened 5 years ago

lulu1315 commented 5 years ago

hello when running the code on one of your example the reflectance is much brighter than the one shown on your project page. data_normal

if you look at the woman trouser for example .. I tried to use -l (even if input is an sRGB image) but it doesn't change much

I'm running on Ubuntu 18.04 so the versions of python modules are much higher than the one required. PIL = 5.1.0 cython = 0.26.1 numpy==1.13.3 scipy==0.19.1 scikit-image==0.14.1 scikit-learn==0.20.2

I had to change on import to have the code running in bell2014/image_util.py :

from skimage.filter import denoise_bilateral

from skimage.restoration import denoise_bilateral

I'm using the default params all the tests I've done so far are giving me a very bright reflectance so I suspect some difference related to the colorspace. thanks in advance for any advice luc

seanbell commented 5 years ago

Hi @lulu1315 -- Not sure how to help you debug. It's possible that scikit-image has some breaking functionality across versions.

Have you tried using a virtualenv with Python2.7 and the package versions from the documentation?

lulu1315 commented 5 years ago

hello Sean thanks for the response. I will do that.thanks