Utils

NRTK perturber CLI Entrypoint

nrtk-perturber

Generate NRTK perturbed images and detections from a given set of source images and COCO-format annotations.

The perturbed images are stored in subfolders named after the chosen perturbation parameter keys and values.

To run the container, use the following command:

docker run -v /path/to/input:/input/:ro -v /path/to/output:/output/ nrtk-perturber [OPTIONS]

The /input/ directory mount will contain all files consumed by the entrypoint script and the /output/ directory will contain all files produced by the entrypoint script.

Command Line Options:

–dataset_dir: Root directory of dataset.

—output_dir: Directory to write the perturbed images to.

–config_file: Configuration file specifying the PerturbImageFactory configuration.

—verbose: Display progress messages. Default is false.

If no command line options are given, the entrypoint script will use the following environment variables as inputs:

INPUT_DATASET_PATH: Root directory of dataset. Default is /input/data/dataset/.

OUTPUT_DATASET_PATH: Directory to write out the perturbed images. Default is /output/data/result/.

CONFIG_FILE: Path to JSON configuration file. Default is /input/nrtk_config.json.

Exits:

101:

COCO annotations file is not found

nrtk-perturber [OPTIONS]

Options

-d, --dataset_dir <dataset_dir>

-o, --output_dir <output_dir>

-c, --config_file <config_file>

-v, --verbose

print progress messages

Environment variables

INPUT_DATASET_PATH

Provide a default for --dataset_dir

OUTPUT_DATASET_PATH

Provide a default for --output_dir

CONFIG_FILE

Provide a default for --config_file

Augmented MAITE dataset(s) generator

Generate augmented dataset(s) of type maite.protocols.object_detection.Dataset.

Generate augmented dataset(s) of type maite.protocols.object_detection.Dataset given an input dataset of the same type and a perturber factory implementation. Each perturber dcombination will result in a newly generated dataset.

Args:

maite_dataset:

A dataset object of type maite.protocols.object_detection.Dataset

perturber_factory:

PerturbImageFactory implementation.

Returns:

A list of tuples containing perturber configurations and augmented datasets

nrtk.entrypoints.nrtk_perturber.__dir__()

Default dir() implementation.

nrtk.entrypoints.nrtk_perturber.__format__(format_spec, /)

Default object formatter.

nrtk.entrypoints.nrtk_perturber.__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

nrtk.entrypoints.nrtk_perturber.__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

nrtk.entrypoints.nrtk_perturber.__reduce__()

Helper for pickle.

nrtk.entrypoints.nrtk_perturber.__reduce_ex__(protocol, /)

Helper for pickle.

nrtk.entrypoints.nrtk_perturber.__sizeof__()

Size of object in memory, in bytes.

nrtk.entrypoints.nrtk_perturber.__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).