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In order to control processing-induced dataset drift we require two ingredients: raw sensor data and an image processing model. This code repository contains the materials for the second ingredient, the image processing models, as well as scripts to load data and run experiments. https://arxiv.org/abs/2211.02578

License: MIT License

Python 97.94% Shell 1.74% Jupyter Notebook 0.32%
distribution shift drift camera optics machine-learning deep-learning deep-neural-networks robustness pytorch

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raw2logit's Issues

ReadMe.md

  • show example how to load processor or task model via uri

demo.py

frontend

  • black buttons

static

  • drone normalization
  • pipeline select instead of step select
  • select two pipelines
  • diff maps (overall, per channel)
  • include downstream task model pred change

forensics

  • ...

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