uzl / inpainting-transformer

Description

This is my implementation of Inpainting Transformer for Anomaly Detection paper [https://arxiv.org/abs/2104.13897]

How to run

First, install dependencies

# tested on Pytorch 1.9
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c 

conda install pytorch-lightning -c conda-forge

conda install piq -c photosynthesis-team -c conda-forge -c PyTorch

Next, run it.

For Training

python training.py --img_root=./dataset/wood/  --gpus=2  --accelerator="ddp"  --batch_size=64  --max_epochs=500  

For inference

Code Structure

The training and inference parts are separated into two files.

1. training.py
2. inference.py (todo)

Training

We use pytorch-lightning for organizing the code.

Training starting point is main() method.