Containerization#

AUKUS Container#

To support users that require tools for an ML T&E workflow, we define a container that would accept an input dataset and apply perturbations to the entire dataset. The perturbed images should be saved to disk and then the container will shut down. In order to support this workflow, the AUKUS container was created.

Given a COCO dataset and an NRTK factory configuration file, the AUKUS container is able to generate perturbed images for each image in the dataset. Each perturbed image will be saved to a given output directory as an individual image file. Once all perturbed images are saved, the container will terminate.

How to Use#

To run the AUKUS container, use the following command: docker run -v /path/to/input:/input/:ro -v /path/to/output:/output/ nrtk-perturber This will mount the inputs to the correct locations and use the nrtk-perturber CLI script with the default args. The CLI script will attempt to load a COCO dataset from the /input/data/dataset/ directory, save perturbed images to /output/data/result/, and load a config file named nrtk_config.json. The dataset directory and nrtk_config.json file must be in the directory mounted to /input/.

Note: Ensure the output directory is writtable by non-root users.

Input Arguments#

The container accepts three input arguments:

  • dataset_dir: input COCO dataset

  • output_dir: directory to store the generated saliency maps

  • config_file: configuration file specifying the PerturbImageFactory params for image perturbation

These can be controlled in two ways: Environment Variables or CLI Options.

The following environment variables are used by default:

  • INPUT_DATASET_PATH: Path to input dataset (default: /input/data/dataset/)

  • OUTPUT_DATASET_PATH: Path to output directory (default: /output/data/result/)

  • CONFIG_FILE: Path to config file (default: /input/nrtk_config.json)

To override defaults, use the -e flag: docker run -e INPUT_DATASET_PATH=/custom/path ... nrtk-perturber

If a user does not want to use environment variables, they can use command line options. After the container name, the user can use the following flags:

  • --dataset_dir or -d: Path to input dataset

  • --output_dir or -o: Path to output directory

  • --config_file or -c: Path to config file

Command line options take precendence over environment variables if both are provided.

Note: The values for dataset_dir and config_file should be written from the perspective of the container (i.e. /path/on/container/dataset_dir/ instead of /path/on/local/machine/dataset_dir/)

Error Codes#

101: Could not identify annotations file for COCO dataset.

Limitations#

Currently, the AUKUS container supports the loading of only COCO datasets. Any existing dataset must be converted to a COCO dataset before using the AUKUS container. Please see KWCOCO documentation for more information on COCO datasets.