Generic augmentations¶

Category: augmentation.vision.2d.training
Version: 1.0.0
UUID: 91a6483d7440fa0664cf1b882b9c190833e859e3ca22b27e6769322badfd6f1c
Execution context: leip_af
Choice Priority: 1000.0

Value Parameters¶

Name	Synonyms	Type	Values	Help
Sequence of augmentations	`augmentation_list`	list	string	This is a sequence of augmentations from the albumentations library. Refer here for more details.

This component fits into¶

Name	UUID	Synonyms
Composite - MixUp Classification	`f19b45...`	`data.augmentation.composite.training`
BYOD from Url - YOLO format	`480e0f...`	`data.augmentation.training`
Smoke (data/sets/url/detection/smoke-pascal-like)	`f549f2...`	`data.augmentation.training`
Zenodo wheat (data/sets/url/detection/zenodo-wheat)	`359e26...`	`data.augmentation.training`
BYOD - RLE format	`0bf531...`	`data.augmentation.training`
Face Mask Detection (data/sets/kaggle/detection/andrewmvd-face-mask-detection)	`770ddd...`	`data.augmentation.training`
Car Detection (data/sets/kaggle/detection/sshikamaru-car-object-detection)	`8c78e8...`	`data.augmentation.training`
GTSRB	`c4039a...`	`data.augmentation.training`
FiftyOne dataset from LakeFS	`be7ad5...`	`data.augmentation.training`
PASCAL VOC	`0fc919...`	`data.augmentation.training`
Composite - Data joiner	`77071f...`	`data.augmentation.composite.joiner.training`
Attach FiftyOne Dataset - detection	`7403de...`	`data.augmentation.training`
Open Images	`eb8f72...`	`data.augmentation.training`
COCO	`6acdcc...`	`data.augmentation.training`
Composite - Data joiner	`b6f994...`	`data.augmentation.composite.joiner.training`
Unlabeled Dataset	`d41459...`	`data.augmentation.training`
Composite - Matting	`8889c0...`	`data.augmentation.composite.matting.training`
Cifar100	`8de396...`	`data.augmentation.training`
FiftyOne dataset from LakeFS - Advanced	`e9fa41...`	`data.augmentation.training`
BYOD from Url - Classification	`8980c6...`	`data.augmentation.training`
BYOD from Url - PASCAL format	`fb4880...`	`data.augmentation.training`
BYOD - COCO format	`b2f2cb...`	`data.augmentation.training`
Attach FiftyOne Dataset - classification	`aada33...`	`data.augmentation.training`
Pothole Detection (data/sets/kaggle/detection/andrewmvd-pothole-detection)	`8e05e3...`	`data.augmentation.training`
MSCOCO	`03465a...`	`data.augmentation.training`
Fire and smoke (data/sets/url/detection/fire-and-smoke-coco-like)	`18fb1b...`	`data.augmentation.training`
BYOD - KITTI format	`2f8623...`	`data.augmentation.training`
PASCAL VOC Segmentation	`2dd717...`	`data.augmentation.training`
BYOD - PASCAL format	`2bd6ce...`	`data.augmentation.training`
Composite - Mosaic	`7bebd5...`	`data.augmentation.composite.training`
SIIM ACR Pneumothorax Segmentation (data/sets/kaggle/detection/jesperdramsch-siim-acr-pneumothorax-segmentation-data)	`05a63c...`	`data.augmentation.training`
CamVid (data/sets/kaggle/segmentation/carlolepelaars-camvid)	`6e8bf3...`	`data.augmentation.training`
Composite - Data joiner	`4e8148...`	`data.augmentation.composite.joiner.training`
Cityscapes Segmentation (data/sets/url/segmentation/cityscapes-segmentation)	`c6c8f1...`	`data.augmentation.training`
BYOD from Url - COCO format	`005947...`	`data.augmentation.training`
Dice, Car, Battery Detection (data/sets/kaggle/detection/kitti-dice-car-battery-detection-new)	`9f11e0...`	`data.augmentation.training`
Drone Segmentation (kaggle/bulentsiyah-semantic-drone)	`96718f...`	`data.augmentation.training`
Smoke Detection (data/sets/kaggle/detection/pascal-smoke-dataset)	`8d5c5a...`	`data.augmentation.training`
Stanford_Cars	`e43b1a...`	`data.augmentation.training`
BYOD from Url - KITTI format	`4c502d...`	`data.augmentation.training`
Imagenette	`9c9749...`	`data.augmentation.training`
Unlabeled Dataset	`214930...`	`data.augmentation.training`
COCO Car Detection (data/sets/kaggle/detection/coco-car-dataset)	`55f1fb...`	`data.augmentation.training`
BYOD - Classification	`409bd8...`	`data.augmentation.training`
FGVC_Aircraft	`ff26bc...`	`data.augmentation.training`
iMaterialist (Fashion) 2019 (data/sets/kaggle/segmentation/competitions-imaterialist-fashion-2019-FGVC6)	`d01f67...`	`data.augmentation.training`
Historical Map Segmentation (data/sets/url/segmentation/historical-map-world-segmentation)	`0cc874...`	`data.augmentation.training`
EuroSAT	`957445...`	`data.augmentation.training`
EuroSAT	`957445...`	`data.augmentation.training`
EuroSAT	`957445...`	`data.augmentation.validation`
Cifar10	`e97b15...`	`data.augmentation.training`
BYOD - YOLO format	`4a5f8d...`	`data.augmentation.training`
Dials and gauges (data/sets/url/detection/dials-and-gauges-pascal-like)	`dbebb1...`	`data.augmentation.training`
Unlabeled Dataset	`3ab62a...`	`data.augmentation.training`
VAID (Overhead Car Detection)	`5659a8...`	`data.augmentation.training`
Fruits Detection (data/sets/kaggle/detection/mbkinaci-fruit-images-for-object-detection)	`db1188...`	`data.augmentation.training`