isaaccorley/deep-aesthetics-pytorch

PyTorch implementation of "Photo Aesthetics Ranking Network with Attributes and Content Adaptation" by Kong et al. (ECCV 2016)

39
/ 100
Emerging

This project helps photographers, marketers, or anyone curating image collections to automatically rank photos based on their aesthetic appeal. You provide a set of images, and it outputs a score for each, indicating how aesthetically pleasing it's likely to be. This is useful for identifying the best photos without manual sorting.

No commits in the last 6 months.

Use this if you need to quickly filter or rank a large volume of images to identify those with high aesthetic quality.

Not ideal if you require subjective aesthetic judgments based on personal taste or specific brand guidelines that deviate from general aesthetic principles.

photography image-curation photo-selection visual-content-evaluation digital-asset-management
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

34

Forks

7

Language

Jupyter Notebook

License

MIT

Last pushed

Feb 15, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/isaaccorley/deep-aesthetics-pytorch"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.