Visual Layer Documentation: Visual Intelligence, At Scale

fastdup supports natively coco annotations. The example below shows how to run bounding box annotations in coco format. (Segmentation masks are not supported yet).

python

# let's get some small dataset to play with
!git clone https://github.com/chongruo/tiny-coco.git

import fastdup
# create a fastdup object 
# input_dir is the location of the images referred in the annotation file. Absolute path please!
# work_dir is the folder containing the resulting outputs
fd = fastdup.create(work_dir='tiny-coco3', input_dir='/kaggle/working/tiny-coco/small_coco/train_2017_small/')

fd.run(annotations='tiny-coco/small_coco/instances_train2017_small.json')

#run any of fastdup galleries 
fd.vis.outliers_gallery()

Full example notebook is here: https://www.kaggle.com/code/graphlab/fastdup-coco-format-tutorial

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