Retrieving Black-box Optimal Images from External Databases (WSDM 2022)
We propose how a user retreives an optimal image from external databases of web services (e.g., Flickr) with respect to user-defined functions (e.g., deep learning-based score functions.)
? Dependency
Please install
wget
andunzip
, e.g., bysudo apt install wget unzip
,- PyTorch from the official website, and
- other dependencies by
pip install -r requirements.txt
.
? Files
download.sh
downloads and preprocesses the Open Image dataset.environments.py
implements wrappers of APIs, i.e., the oracles in the paper.evaluate.py
is the evaluation script.methods.py
implements Tiara, Tiara-S, and baseline methods.openimage_feature_extract.py
preprocess the Open Image dataset. Please run this script after you download images. This script is automatically run bydownload.sh
.preprocess_openimage.py
preprocess the Open Image dataset. Please run this script before you download images. This script is automatically run bydownload.sh
.utils.py
implements miscellaneous functions, i.e., the word embbeding loader.
?️ Download and Preprocess Datasets
$ bash ./download.sh
? Evaluation
Try with Open Image datasets by
$ python evaluate.py --env open --verbose --num_seeds 1 -c 0
The results are saved in outputs
directiory.
Please refer to the help command for further options.
$ python evaluate.py -h
usage: evaluate.py [-h] [--tuning] [--extra] [--env {open,flickr,flickrsim}]
[--num_seeds NUM_SEEDS] [--budget BUDGET]
[--api_key API_KEY] [--api_secret API_SECRET]
[--font_path FONT_PATH] [--verbose]
[-c [CLASSES [CLASSES ...]]]
optional arguments:
-h, --help show this help message and exit
--tuning
--extra
--env {open,flickr,flickrsim}
--num_seeds NUM_SEEDS
--budget BUDGET
--api_key API_KEY API key for Flickr.
--api_secret API_SECRET
API secret key for Flickr.
--font_path FONT_PATH
Font path for wordclouds.
--verbose
-c [CLASSES [CLASSES ...]], --classes [CLASSES [CLASSES ...]]
Flickr API
The Flickr experiments require a Flickr API key. Please get a key from .
?️ Citation
@inproceedings{sato2022retrieving,
author = {Ryoma Sato},
title = {Retrieving Black-box Optimal Images from External Databases},
booktitle = {Proceedings of the Fifteenth {ACM} International Conference on Web Search and Data Mining, {WSDM}},
year = {2022},
}