Example Non AI Template

This repository is an example template of what a project could look like. It uses the tinygltf header to parse and load a input gltf file for both encoder and decoder.

You can use this repository as a reference or starting point for your project.

Creating Your Repository

Create a new repository for your project within this GitHub organization. You can use the Use this template button on GitHub to create a copy of this repository for your team. Use your team name for the repository name and make sure all your team members have access to your repository. To add them go to Settings then Collaborators and teams.

Then set up your new repository locally. You can clone it or use GitHub Desktop. Both options are available on the Code dropdown menu. To clone your repository and checkout the submodules use the following Git commands.

git clone [YourRepositoryGitURL]
cd [YourRepositoryName]
git submodule update --init --recursive

Now you are ready to start building your solution.

Building the Executables

Run the scripts/build_non_ai.sh script to build the executables.

bash scripts/build_non_ai.sh

This is just a template, you need to write your own code to compress and decompress the .obj or .glTF sample files.

The build script creates the following symlinks to the executables so that the test script can run them.

• encoder this points to the build/bin/encoder executable.
• decoder this points to the build/bin/decoder executable.

If you want to create your own build script you can copy scripts/build_non_ai.sh outside the scripts folder (you cannot modify the scripts folder). Make sure to also update the .github/workflows/ci.yml file to run your new script on GitHub Actions.

Testing the Executables

The scripts/test_non_ai.sh script runs all the sample models through the encoder and decoder.

bash scripts/test_non_ai.sh

The test script measures the compression ratio, decompression time and image quality for each sample model and then calculates a weighted average score.

It writes the compressed and decompressed files to the test folder.

And it logs the values for each model to the log files.

• test/compression.log the format is Encoded/Failed FilePath CompressionRatio
• test/decompression.log the format is Decoded/Failed FilePath DecompressionTime
• test/quality.log the format is Quality/Failed FilePath PSNR

Support

Check the FAQs

If you still have any questions or experience any problems please reach out to us on the #support channel on Slack.