The purpose of this notebook is to provide options for exploring large image datasets, through use of K nearest neighbour graphs and other methods. It aims to be a base for further development in future.
This notebook ingests a zip file containing images, and returns a HTML file (giving options for visual exploration of the dataset), and provides some basic visualisations.
-
Centre for Digital Cultures and Societies
-
Language Data Commons of Australia
A. Radford et al. (2021). Learning Transferable Visual Models From Natural Language Supervision. OpenAI. https://arxiv.org/pdf/2103.00020
Brankica Bratić, Michael E. Houle, Vladimir Kurbalija, Vincent Oria, and Miloš Radovanović. (2018). NN-Descent on High-Dimensional Data. In WIMS’18: 8th International Conference on Web Intelligence, Mining and Semantics, June 25–27, 2018, Novi Sad, Serbia. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3227609.3227643
J. Burgess et al. (2021). Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms. https://osf.io/preprints/socarxiv/2cwsu_v1
K Simonyan, A Zisserman. (2015). Very Deep Convolutional Neural Networks for Large Scale Image Recognition. ICLR 2015. https://doi.org/10.48550/arXiv.1409.1556