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Geometrical Homogeneous Clustering for Image Data Reduction. An algorithm to reduce large image datasets maintaining similar accuracy.

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GHCIDR 🌟

This code is for the SubsetML ICML 2021 Workshop paper - "Geometrical Homogeneous Clustering for Image Data Reduction"

Requirements

Please download the required modules from the requirements.txt

pip install -r requirements.txt

To create the reduced data

For creating reduced dataset change <dataset> to MNIST/FMNIST/CIFAR10.

For RHC(baseline)

python main.py -variantName RHC -datasetName <dataset>

For RHCKON

python main.py -variantName RHCKON -datasetName <dataset> -KFarthest <K>

For KONCW

python main.py -variantName KONCW -datasetName <dataset> -alpha <alpha>

For CWKC

python main.py -variantName CWKC -datasetName <dataset> -alpha <alpha>

For GHCIDR

python main.py -variantName GHCIDR -datasetName <dataset> -alpha <alpha>

The reduced dataset will be saved in "./datasetPickle" with the name <datasetName>_<variantName>.pickle

To test the reduced data

For testing the reduced dataset <dataset> with variant <variant> change <modelname> to vgg1/fcn.

python vgg1.py -datasetName <dataset> -variantName <variant> -epochs 100 -lr 0.01 -batchSize 64 -fullDataset No

Team Members 🧍

The contributors of this project -

Devvrat Joshi
Janvi Thakkar
Shril Mody
Siddharth Soni

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