Annotated Flickr dataset for identification of professional photographers

Published: 11 July 2022| Version 1 | DOI: 10.17632/2nc8ytfw5x.1
Rubén Gaspar Marco, Sofia Strukova, José Ruipérez Valiente, Felix Gomez Marmol


The dataset consists of two collections, namely, users' features and photos' features. Specifically, we have collected 2,647,928 photos uploaded by 27,516 unique users to Flickr, with an average of 96 photos per user and 100 photos for more than 90% of users. Apart from the data directly collected from Flickr, the dataset has been enriched with new features that allow the analysis performed in the associated research article. One of the most valuable features of this data collection is that each photo has three Image Quality Assessment scores representing aesthetic and technical aspects. For this, we used Convolutional Neural Networks trained with human-labeled data. Furthermore, we added labels to indicate whether the user is a professional photographer, so the data are specially prepared for supervised training.


Steps to reproduce

The associated article with the same title as this repository documents the necessary steps for its reproduction and, as it is commented in it, in the linked GitHub repository is all the necessary code to do it.


Universidad de Murcia


Photography, Image Quality, Social Network