Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/scottworkman/deephorizon
https://github.com/scottworkman/deephorizon
Last synced: 3 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/scottworkman/deephorizon
- Owner: scottworkman
- Created: 2016-08-26T23:48:13.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2022-04-28T17:26:09.000Z (over 2 years ago)
- Last Synced: 2024-04-10T14:50:47.003Z (7 months ago)
- Language: Python
- Size: 256 KB
- Stars: 38
- Watchers: 3
- Forks: 14
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-CoreML-Models - deephorizon
README
# Introduction
This repository contains the model files, solver definitions, and
learned weights for the networks described in the following
publication:> Horizon Lines in the Wild (Scott Workman, Menghua Zhai, Nathan Jacobs), In
> British Machine Vision Conference (BMVC), 2016.
> [pdf](http://hlw.csr.uky.edu)```
@inproceedings{workman2016horizon,
author={Workman, Scott and Zhai, Menghua and Jacobs, Nathan},
title={Horizon Lines in the Wild},
booktitle={{British Machine Vision Conference (BMVC)}},
year={2016}
}
```## Getting Started
Download the model required for the demo:
```cd models; ./download_models.sh --demo```
Run the demo:
```cd example; python example.py```
To download all models:
```cd models; ./download_models.sh```
## License
This software is released under a creative commons license which
allows for personal and research use only. For a commercial license
please contact the authors. You can view a license summary here:
http://creativecommons.org/licenses/by-nc/4.0/## Contact
Scott Workman
University of Kentucky
http://cs.uky.edu/~scott/