This repository provides the experiments conducted for the Maximum Weight Entropy method (MaxWEnt) within the OpenOOD Benchmark.
The OpenOOD Benchmark reproduces representative methods within the Generalized Out-of-Distribution Detection Framework
,
aiming to make a fair comparison across methods that initially developed for anomaly detection, novelty detection, open set recognition, and out-of-distribution detection.
To setup the environment, we use conda
to manage our dependencies.
Our developers use CUDA 10.1
to do experiments.
You can specify the appropriate cudatoolkit
version to install on your machine in the environment.yml
file, and then run the following to create the conda
environment:
conda env create -f environment.yml
conda activate openood
Datasets and pretrained models are provided here. Please unzip the files if necessary.
The codebase accesses the datasets from ./data/
and pretrained models from ./networks/
by default.
The scripts to run the MaxWEnt experiments can be found in the ./mwe_scripts/
folder.