A poetic machine-learning dataset made of 5,000 images of found pebbles. Mimicking the datasets used to train computer vision systems, this project is an intervention that highlights the things we ignore when recording and classifying the world through data. Primarily sited as a repository on the code-sharing site Github, this project is also shown as a print of all the pebbles in the dataset sorted by visual similarity and a video.
Created while a Visiting Fellow (King's College) and artist-in-residence (Computer Laboratory) at University of Cambridge.
PEBBLE DATASET
Print: 60x60" (152x152cm)
Video: 12 minutes
machine learning, pebble, found, Python, website, Github, data
Github repository for this project