Add Docker Utility Images & Flask API Wrapper based on Plattar/xr-utils for Converters and Optimizers

[Schlomoh]

We are extending our open-source 3D project by introducing Docker images to streamline deployment, both locally and on cloud platforms such as Google Cloud Run. The goal is to create converter Docker images and a Python Flask API wrapper to expose these converters via an API, making them more accessible and composable. We'll use the Plattar/xr-utils as a base, which already integrates tools like Assimp, Apple’s ARKit, and Google’s USD/GLTF converters, and expand on this by improving modularity and accessibility.

Task Breakdown:

1. Base on Plattar/xr-utils:

• Leverage the existing Plattar/xr-utils Docker image that bundles tools such as Assimp, USDZ conversion, and GLTF utilities for AR and 3D file conversion.
• Build upon this by making the converters more composable, allowing for independent and flexible use of each tool within Docker or cloud environments.

2. Docker Utility Images:

• Create individual, modular Docker images for various converter and optimizer tools.
• Ensure these images can be launched easily into Docker containers and deployed to cloud platforms like Google Cloud Run.
• Optimize for both local development and cloud deployment.

4. Python Flask API Wrapper:

• Develop a Docker image for a Python Flask API that wraps the converter and optimizer tools.
• This API should expose endpoints to trigger specific conversions, enabling easier integration into other applications.
• Orchestrate the workflow between the utility images, providing a unified API interface.

6. Integration and Deployment:

• Set up the API wrapper and utility images on a cloud service, such as Google Cloud Run.
• Provide full documentation for API endpoints, Docker image usage, and cloud deployment processes.

Acceptance Criteria:

• Docker images based on Plattar/xr-utils are created, with enhanced composability and accessibility.
• A Python Flask API wrapper is built to manage and expose the functionality of these images.
• The solution should be deployable locally and on cloud platforms (Google Cloud Run).
• Complete documentation is provided for usage and deployment.

Additional Considerations:

• Ensure the Docker images follow best practices for security and performance.
• Focus on making the images modular and easily updatable to support future conversions and optimizations.