Installing zamba
¶
Zamba has been developed and tested on macOS and Ubuntu Linux for both CPU and GPU configurations.
To install zamba
¶
1. Install prerequisites¶
Prerequisites:
- Python 3.7 or 3.8
- FFmpeg
Python 3.7 or 3.8¶
We recommend Python installation using Anaconda for all platforms. For more information about how to install Anaconda, here are some useful YouTube videos of installation:
FFmpeg version 4.3¶
FFmpeg is an open source library for loading videos of different codecs. Using FFmpeg means that zamba
can be flexible in terms of the video formats we support. FFmpeg can be installed on all different platforms, but requires some additional configuration depending on the platform. Here are some videos and instructions walking through FFmpeg installation:
-
- In the command line, enter
sudo apt update
and thensudo apt install ffmpeg
.
- In the command line, enter
- MacOS install video
- First, install Homebrew. Then run
brew install ffmpeg
- First, install Homebrew. Then run
To check that FFmpeg
is installed, run ffmpeg
:
$ ffmpeg
ffmpeg version 4.4 Copyright (c) 2000-2021 the FFmpeg developers
built with Apple clang version 12.0.0 (clang-1200.0.32.29)
...
To check your installed version, run ffmpeg -version
.
2. Install zamba
¶
On macOS, run these commands in the terminal (⌘+space, "Terminal"). On Windows, run them in a command prompt, or if you installed Anaconda an anaconda prompt (Start > Anaconda3 > Anaconda Prompt).
To install for development:
$ pip install zamba
To check what version of zamba you have installed:
$ pip show zamba
To update zamba to the most recent version if needed:
$ pip install -U zamba
Operating Systems that have been tested¶
macOS¶
zamba
has been tested on macOS High Sierra.
Linux¶
zamba
has been tested on Ubuntu versions 16 and 17.
Windows¶
zamba
has been tested on Windows 10.
Using GPU¶
zamba
is much faster on a machine with a graphics processing unit (GPU), but has also been developed and tested for machines without GPU(s).
To use a GPU, you must be using an NVIDIA GPU, have installed and configured CUDA, and have installed and configured CuDNN per their specifications.