This repository contains Julia implementation of visual_atomic_renderer/render_VisualAtom.py
, originally implemented in Python. The original Python implementation can be found at masora1030/CVPR2023-FDSL-on-VisualAtom
To use this Julia implementation, you will need:
- Julia version ≥ 1.8
- Clone this repository:
$ git clone https://github.com/AtelierArith/VisualAtom.jl.git
- Change directory into the repository:
$ cd VisualAtom.jl
- Install the required Julia packages:
$ julia --project=@. -e 'import Pkg; Pkg.instantiate()'
Activating project at `~/work/atelier_arith/VisualAtom.jl`
Precompiling project...
Progress [> ] 0/1
◓ VisualAtom
Easy! Just run:
$ julia --project=@. --procs auto run.jl
It will create a directory VisualAtom_dataset
by default and 1000 * 1000 images will be generated.
The following screenshot was captured while running on iMac 2019 with --procs 16
.
If you are surprised by these results, you may want to consider moving from Python to Julia.
--procs {N|auto}
Integer value N launches N additional local worker processes "auto" launches as many workers as the number of local CPU threads (logical cores)
Having trouble installing Julia? You can save yourself the trouble of installation by using a Docker container.
$ make && docker compose run --rm shell julia -p auto run.jl
This project is licensed under the MIT License. See the LICENSE file for details.
- The original Python implementation: https://github.com/masora1030/CVPR2023-FDSL-on-VisualAtom
- The authors of the CVPR 2023 paper for their novel work on the FDSL algorithm
- The authors of Perlin noise library for Python: https://github.com/caseman/noise
- JuliaLang and its community
- ChatGPT-3.5/ChatGPT-4