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Extending CLIP for Category-to-Image Retrieval in E-commerce

This repository contains the code used for the experiments in "Extending CLIP for Category-to-image Retrieval in E-commerce" published at ECIR 2022.

License

The contents of this repository are licensed under the MIT license. If you modify its contents in any way, please link back to this repository.

Reproducing Experiments

First off, install the dependencies:

pip install -r requirements.txt

Download the data

Download the CLIP_data.zip from this repository.

After unzipping CLIP_data.zip put the resulting data folder in the root:

data/
    datasets/
    results/

Evaluate the model

sh jobs/evaluation/evaluate_cub.job
sh jobs/evaluation/evaluate_abo.job
sh jobs/evaluation/evaluate_fashion200k.job
sh jobs/evaluation/evaluate_mscoco.job
sh jobs/evaluation/evaluate_flickr30k.job
# printing the results for CLIP in one file
sh jobs/postprocessing/results_printer.job

Citing and Authors

If you find this repository helpful, feel free to cite our paper "Extending CLIP for Category-to-image Retrieval in E-commerce":

@inproceedings{hendriksen-2022-extending-clip,
author = {Hendriksen, Mariya and Bleeker, Maurits and Vakulenko, Svitlana and van Noord, Nanne and Kuiper, Ernst and de Rijke, Maarten},
booktitle = {ECIR 2022: 44th European Conference on Information Retrieval},
month = {April},
publisher = {Springer},
title = {Extending CLIP for Category-to-image Retrieval in E-commerce},
year = {2022}}