https://github.com/ap6yc/deepart
https://github.com/ap6yc/deepart
Last synced: 6 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/ap6yc/deepart
- Owner: AP6YC
- License: cc0-1.0
- Created: 2021-09-17T20:41:57.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2025-03-12T05:23:47.000Z (over 1 year ago)
- Last Synced: 2025-03-12T05:25:45.518Z (over 1 year ago)
- Language: Julia
- Size: 15.7 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
[][docs-url]
A repository containing implementations and experiments for the upcoming paper _Deep Adaptive Resonance_.
| **Documentation** | **Testing Status** | **Zenodo DOI** |
|:-----------------:|:------------------:|:--------------:|
| [![Docs][docs-img]][docs-url] | [![CI Status][ci-img]][ci-url] | [![DOI][zenodo-img]][zenodo-url] |
[zenodo-img]: https://zenodo.org/badge/DOI/10.5281/zenodo.10896042.svg
[zenodo-url]: https://zenodo.org/doi/10.5281/zenodo.10896042
[ci-img]: https://github.com/AP6YC/DeepART/workflows/CI/badge.svg
[ci-url]: https://github.com/AP6YC/DeepART/actions?query=workflow%3ACI
[docs-img]: https://img.shields.io/badge/docs-blue.svg
[docs-url]: https://AP6YC.github.io/DeepART/
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Basic Usage](#basic-usage)
- [Python](#python)
- [Attribution](#attribution)
- [Authors](#authors)
- [Datasets](#datasets)
- [Assets](#assets)
- [Quotes](#quotes)
[julia-lang]: https://julialang.org/
[julia-docs]: https://docs.julialang.org/en/v1/
[drwatson-docs]: https://juliadynamics.github.io/DrWatson.jl/dev/
## Basic Usage
For detailed usage, please read the [documentation][docs-url].
The `DeepART` project is a [`Julia`][julia-lang] project, so its use follows typical [Julia][julia-docs] usage.
The `DeepART` project also utilizes [`DrWatson.jl`][drwatson-docs] for organizing and running simulations.
The library code for the project is contained in `src/`, while all experiments are enumerated in `scripts`.
Each folder therein contains a simple README for the order of running experiments.
For example, after installing Julia on your system, you instantiate this project with
```julia
using Pkg; Pkg.activate(); Pkg.instantiate()
```
and run an experiment interactively with
```julia
include("scripts/1_baselines/single/conv.jl")
```
or through the terminal with
```shell
julia --project="." "scripts/1_baselines/single/conv.jl"
```
## Python
The Python component of this project can be installed on `python=3.12` with
```sh
pip install -r requirements
```
or in editable mode with
```sh
pip install -e "./src/deepart
```
## Attribution
### Authors
- Sasha Petrenko - - [@AP6YC](https://github.com/AP6YC)
### Datasets
- [Indoor Scene Recognition](https://web.mit.edu/torralba/www/indoor.html)
- [Direct Link](http://groups.csail.mit.edu/vision/LabelMe/NewImages/indoorCVPR_09.tar)
### Assets
- [Deep-learning icons created by Freepik - Flaticon](https://www.flaticon.com/free-icons/deep-learning) ([deep-learning_2080961](https://www.flaticon.com/free-icon/deep-learning_2080961))
- [Unlearned Font](https://www.1001fonts.com/unlearned-font.html)
### Quotes
> To achieve great things, two things are needed: a plan and not quite enough time
>
> -- Leonard Bernstein