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License: GNU General Public License v2.0
Framework to train semantic segmentation models on Pytorch using yaml config files
License: GNU General Public License v2.0
There is bug in class_freq computation, more specifically, reading value of class_freq from generated csv dataset.
In here, the value of class freq for segmentation mask is read from df.columns, but this value in csv is somehow computed from image array as follows. This lead to NaN or negative loss during training, because here sum of the class_freq was larger than 1.
My temporary solution was to ignore class_freq column from csv file here
Hi,
thanks for great framework! However there is huge fundamental bug in FrameField approach.
First here
crossfield is treated as mask during loading, thus, in here all anglefield are vanished and set to value one.
Moreover, any affine augmentation from albumentation is not usable, because anglefield has to be treated in different way for affine transformations, as in the original FrameField repo f.e. rotate_anglefield
Am I right?
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