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An ORM built to simplify working with datasets in COCO format.

Project description

coco_orm

coco_orm is an ORM built to simplify working with datasets in COCO format.

Examples

Create a new annotations file and fill it with data in COCO format:

from coco_orm import CocoDataset
from coco_orm.models import Image, Category, Annotation

# create an annotations.json file containing COCO dataset annotations.
coco_dataset = CocoDataset(".../dataset/annotations.json")

# create a new image
image = Image(id=1, file_name="01.jpg", width=320, height=320)
coco_dataset.images.append(image)

# create a new category
category = Category(id=1, name="cat")
coco_dataset.categories.append(category)

# create a new annotation
annotation = Annotation(image_id=1, category_id=1, bbox=[260, 177, 231, 199])
coco_dataset.annotations.append(annotation)

# save to the .json file
coco_dataset.save()

Apply filters to the COCO dataset collections

from coco_orm import CocoDataset
from coco_orm.filters import ImageFilters

# read annotations file
coco_dataset = CocoDataset(".../dataset/annotations.json")

# filter an image collection by ids
image_filters = (ImageFilters().ids([1, 3]))
coco_dataset.images.filter(image_filters, inplace=True)

# save filtered dataset to the separate file
coco_dataset.save(".../dataset/filtered_annotations.json")

Further info

Created by a team of Computer Vision enjoyers of Igor Sikorsky Kyiv Polytechnic Institute.

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