Asset-Frameworker/Documentation/01_User_Guide/10_Docker.md

User Guide: Docker

This document explains how to use the Asset Processor Tool with Docker.

Overview

A Dockerfile and requirements-docker.txt are provided to allow you to build and run the Asset Processor Tool in a containerized environment. This is primarily intended for CLI or monitor usage.

Building the Docker Image

From the project root directory, run the following command to build the Docker image:

docker build -t asset-processor-tool .

This command builds a Docker image named asset-processor-tool using the Dockerfile in the current directory.

Running the Docker Container

You can run the Docker container using standard Docker commands. You will typically need to mount volumes to make your input assets and desired output directory accessible within the container.

Here is an example run command (adjust volumes as needed):

docker run -v /path/to/your/inputs:/data/input -v /path/to/your/outputs:/data/output asset-processor-tool python main.py /data/input/YourAsset.zip -p YourPreset

• -v /path/to/your/inputs:/data/input: This mounts your local input directory (/path/to/your/inputs) to the /data/input directory inside the container.
• -v /path/to/your/outputs:/data/output: This mounts your local output directory (/path/to/your/outputs) to the /data/output directory inside the container.
• asset-processor-tool: The name of the Docker image to run.
• python main.py /data/input/YourAsset.zip -p YourPreset: The command to execute inside the container. This example runs the CLI with a specific input file and preset, using the mounted input and output directories.

Adjust the input file path (/data/input/YourAsset.zip) and preset name (YourPreset) as needed for your specific use case. You can also adapt the command to run the monitor.py script within the container.