Art from the Machine
Overview
ArsMachina is a Python package that infuses modern machine‑learning techniques into visual‑effects (VFX) and digital‑art pipelines. Whether you are a VFX artist looking to automate labor‑intensive tasks or a technical director eager to prototype generative tools, ArsMachina delivers a friendly, modular toolbox for creating art and beauty from the machine.
With an emphasis on usability, extensibility, and GPU performance, arsmachina provides ready‑made operators, utilities, and tutorials that make it easy to weave ML into Houdini, Blender, Nuke, and other industry staples.
Features
- Pre‑built Models & Utilities – Object detection, image segmentation, latent‑diffusion style transfer, and more, tuned for VFX needs.
- Seamless DCC Integration – Drop‑in wrappers for Houdini TOPs, Blender Python, and Nuke Gizmos.
- GPU Acceleration – Optimised kernels using PyTorch + CUDA so you spend time iterating, not waiting.
- Tutorials & Example Notebooks – Hands‑on guides that walk you from "Hello Tensor" to production‑ready FX shots.
- Extensible Architecture – Clear entry points for plugging in your own datasets, models, and node flavours.
Why ArsMachina?
Machine learning has opened new creative frontiers—auto‑rotoscoping entire plates, synthesising photoreal textures, or animating crowds at the click of a button. arsmachina aims to:
- Empower VFX professionals with accessible ML primitives.
- Provide a playground for experimenting with generative and analytical techniques.
- Lower the barrier to entry so artists can focus on storytelling instead of boilerplate code.
Getting Started
Installation
Clone the repository and install locally:
git clone https://github.com/suhailphotos/ArsMachina.git
cd ArsMachina
pip install .
or add it to a Poetry‑managed project:
poetry add arsmachina
Python ≥ 3.12 and a recent CUDA‑enabled GPU are recommended for full functionality.
Resources
- Documentation – API reference and guides live in the
docs/folder. - Examples – Real‑world notebooks reside in the upcoming course repository
ml4Vfx. - Community – Open a Discussion or file an Issue—contributions and ideas are welcome!
Contributing
Bug fixes, new operators, and tutorial notebooks are all appreciated. Please read CONTRIBUTING.md for coding standards and a quick start on setting up a dev environment.
License
Released under the MIT License. See LICENSE for details.
Stay Connected
- Author Suhail
- GitHub https://github.com/suhailphotos/ArsMachina
Metadata
Release files for arsmachina 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| arsmachina-0.1.0.tar.gz | 2.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| arsmachina-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.1 kB
Release files / arsmachina-0.1.0.tar.gz
| Download URL | arsmachina-0.1.0.tar.gz |
|---|---|
| Size | 2.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.3 CPython/3.12.3 Linux/6.8.0-59-generic
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Release files / arsmachina-0.1.0-py3-none-any.whl
| Download URL | arsmachina-0.1.0-py3-none-any.whl |
|---|---|
| Size | 3.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.3 CPython/3.12.3 Linux/6.8.0-59-generic
|