artus.inference package

Submodules

artus.inference.config module

artus.inference.deploy_unlabeled_dataset module

Create a fiftyone dataset with unlabeled or labeled images.

artus.inference.deploy_unlabeled_dataset.create_or_load_dataset(dataset_name, dataset_type=['unlabeled', 'coco'], images_path=None, annotations_path=None, df_test=None, label_type=['segmentations', 'detections'])

Create a fiftyone labeled or unlabeled dataset.

If the dataset_name provided is in the local 51 database : the dataset is loaded from the database otherwise, the dataset is created

Parameters:

• dataset_name (str) – the name of the dataset that you want to create or load

• dataset_type (str) – can be ‘unlabeled’ for images without annotations or ‘coco’ if images have coco annotations.

• images_path (str) – a path to the directory containing the images (can be tif, png or jpg images)

• annotations_path (str, optional) – a path to the COCO annotations files

• df_test (str, optional) – a path to the COCO annotations files for test images

• label_type – ‘segmentations’ for mask or ‘detections’ for bounding box annotations

Returns :

A fiftyone.core.dataset with at least 6 fields : id, coco_id, filepath, ground_truth annotations (if provided), tags and basic metadata.

artus.inference.predict module

Module contents