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I noticed in damage_inference.py that the testing images are all scaled by 1.4. Inside damage_classification.py however the images are all scaled by 1/255 which makes sense to me.
The performance of the pretrained model changes greatly depending on the choice of scaling I've noticed. When I change the scaling to 1/255 the model only predicts "no-damage" but when you keep the scaling as 1.4 the results are more similar to the paper.
The text was updated successfully, but these errors were encountered:
Michaeljurado42
changed the title
Potential bug in scaling code in damange_inference.py
Potential bug in scaling in damange_inference.py
Sep 12, 2021
I noticed in damage_inference.py that the testing images are all scaled by 1.4. Inside damage_classification.py however the images are all scaled by 1/255 which makes sense to me.
The performance of the pretrained model changes greatly depending on the choice of scaling I've noticed. When I change the scaling to 1/255 the model only predicts "no-damage" but when you keep the scaling as 1.4 the results are more similar to the paper.
The text was updated successfully, but these errors were encountered: