Introduction

Tools for Computer Vision Pipelines

See documentation for details.

See image notebook for a demo of the Image class.

See channel notebook for a demo of channel operators.

See draw notebook for a demo of draw operators.

See edit notebook for a demo of edit operators.

See filter notebook for a demo of filter operators.

Installation for Developers

Docker

1. Install docker-desktop
2. Ensure docker-desktop has at least 4 GB of memory allocated to it.
3. git clone git@github.com:theNewFlesh/cv-depot.git
4. cd cv-depot
5. chmod +x bin/cv-depot
6. bin/cv-depot docker-start
   • If building on a M1 Mac run export DOCKER_DEFAULT_PLATFORM=linux/amd64 first.

The service should take a few minutes to start up.

Run bin/cv-depot --help for more help on the command line tool.

ZSH Setup

1. bin/cv-depot must be run from this repository's top level directory.

2. Therefore, if using zsh, it is recommended that you paste the following line in your ~/.zshrc file:

   • alias cv-depot="cd [parent dir]/cv-depot; bin/cv-depot"
   • Replace [parent dir] with the parent directory of this repository

3. Consider adding the following line to your ~/.zshrc if you are using a M1 Mac:

   • export DOCKER_DEFAULT_PLATFORM=linux/amd64

4. Running the zsh-complete command will enable tab completions of the cli commands, in the next shell session.

   For example:

   • cv-depot [tab] will show you all the cli options, which you can press tab to cycle through
   • cv-depot docker-[tab] will show you only the cli options that begin with "docker-"

Installation for Production

Python

pip install cv-depot

If you are on Debian-based Linux and you run into C library issues such as with OpenEXR, the following may help:

apt update && \
apt install --fix-missing -y python3.13-dev && \
apt install -y \
    build-essential \
    g++ \
    gcc \
    zlib1g-dev

For OpenEXR you will also need this:

apt install -y \
    libopenexr-dev \
    openexr

For FFMPEG you will also need this:

apt install -y ffmpeg

Please see the prod.dockerfile for an official example of how to build a docker image with cv-depot.

Docker

1. Install docker-desktop
2. docker pull theNewFlesh/cv-depot:[mode]-[version]

Quickstart Guide

This repository contains a suite commands for the whole development process. This includes everything from testing, to documentation generation and publishing pip packages.

These commands can be accessed through:

• The VSCode task runner
• The VSCode task runner side bar
• A terminal running on the host OS
• A terminal within this repositories docker container

Running the zsh-complete command will enable tab completions of the CLI. See the zsh setup section for more information.

Command Groups

Development commands are grouped by one of 10 prefixes:

Common Commands

Here are some frequently used commands to get you started:

Development CLI

bin/cv-depot is a command line interface (defined in cli.py) that works with any version of python 2.7 and above, as it has no dependencies. Commands generally do not expect any arguments or flags.

Its usage pattern is: bin/cv-depot COMMAND [-a --args]=ARGS [-h --help] [--dryrun]

Commands

The following is a complete list of all available development commands:

Flags

Production CLI

cv-depot comes with a command line interface defined in command.py.

Its usage pattern is: cv-depot COMMAND [ARGS] [FLAGS] [-h --help]

Commands

bash-completion

Prints BASH completion code to be written to a _cv-depot completion file

Usage: cv-depot bash-completion

zsh-completion

Prints ZSH completion code to be written to a _cv-depot completion file

Usage: cv-depot zsh-completion