- https://github.com/Benjamin-Loison
- Joined on
2022-10-16
datasets/android/
To test faster directly evaluate the whole dataset instead of an increasing one.
In theory Rafael images are more controlled, so less noise and RAISE different noise so not similar.
Normalization across cameras mey be incorrect if do not sample in general in same range.
Debugging always guessing Rafael by just providing a set of 2 images, one training and one testing being the same one.
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minColor
and maxColor
(#63)
attribute_source_camera.py
Will we face normalization issue as do not know what normalization to apply to a testing image as we do not know the associated device in theory?
Well can apply a single normalization for both…
Considering same number of images for both groups and consider half for testing and up to the other half for training. Just a 2D curve seems enough to represent the accuracy, y-axis being accuracy…
split_and_compare_prnus_of_subgroups.py
compatible with RAW images
raw_image_visible
what is the _visible
for?
Related to issues/25#issuecomment-1476.
plt.imsave
as do not seem necessary anymore