Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/parkerbritt/cog

Pipeline tool for, Rebirth, university short film
https://github.com/parkerbritt/cog

animation cgi perforce python qt vfx vfx-pipeline

Last synced: 9 days ago
JSON representation

Pipeline tool for, Rebirth, university short film

Awesome Lists containing this project

README

        




Cog Pipeline








Cog is a **pipeline interface for VFX** and animation specifically designed for the needs of the team of the **Rebirth** student film.
Because Cog is tailoured to our team's specific needs and built around other tools, it may not fit all use cases or environments.

![image](screenshots/main_interface.jpg)
> **Warning**
> Cog is in a very early stage of development. It likely will never be in a state to be used publicly.

## Features
- **Cross platform**
- Cog was built to work across **Windows and Linux**. Mac is not supported.
- Packaged with PIP
- Interface built with Qt for Python
- **Rendering**
- Local rendering using headless Houdini instances
- Select individual layers to render
![image](screenshots/render_demo.gif)
- **Project Environment Variables**
- Environment envariables are set when opening project files (Houdini, Maya, Nuke, etc.)
- Frame range, shot number, fps, description, etc.
- **Search**
- Users are able to search for specific assets or shots
- **Shot Management**
- Shots can be created, edited, or deleted through the interface
- **Auto Update**
- Cog will automatically check for new package versions on your perforce repository and install the latest version
- **Environment Setup**
- On the first launch Cog will setup the user's envrionment to enable the rest of the pipeline:
- creating config files, installing houdini packages, setting environment variables, installing python modules for the houdini python interpreter, etc.

## Installation
### Requirements
- Perforce P4
- Sidefx Houdini

First **clone** and **cd** into the repository
```bash
git clone https://github.com/parkerbritt/cog
cd cog
```
### (Option 1) Interactive installation
Run the **install** command
```bash
pip install -e .
```
### (Option 2) Regular installation
**Build and install** the tar.gz package
```bash
python setup.py sdist
pip install dist/cog_vfx-0.1.tar.gz
```
### Launch Cog
**Run** the cog **command*** in the terminal
```bash
cog
```
You can also create **.desktop** file or **Windows shortcut** to make accessing cog easier