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Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

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black blackdoc flake8 isort mypy

PyTorch re-implementation of


1. AUROC Scores

category Paper My Implementation
zipper - -
wood - -
transistor - -
toothbrush - -
tile - -
screw - -
pill - -
metal_nut - -
leather - -
hazelnut - -
grid - -
carpet - -
capsule - -
cable - -
bottle - -

2. Graphical Results

zipper

wood

transistor

toothbrush

tile

screw

pill

metal_nut

leather

hazelnut

grid

carpet

capsule

cable

bottle


3. Requirements

  • CUDA 10.2
  • nvidia-docker2

4. Usage

a) Download docker image and run docker container

docker pull taikiinoue45/mvtec:nfad
docker run --runtime nvidia -it --workdir /app --network host taikiinoue45/mvtec:nfad /usr/bin/zsh

b) Download this repository

git clone https://github.com/taikiinoue45/NFAD.git
cd /app/NFAD/nfad

c) Run experiments

sh run.sh

d) Visualize experiments

mlflow ui

5. Contacts

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Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

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