Image annotation file operation provider. [Documentation](https://imgann.readthedocs.io/en/latest/index.html)
Project description
Python library for annotation file conversion and preview.
Installation
- From PiPy You can install the Real Python Feed Reader from PyPI:
$ pip install imgann
The package is support Python 3.7 and above.
- From github clone the codebase from GitHub
$ git clone https://github.com/nipdep/imgann.git
build the library
$ python setup.py bdist_wheel sdist
install built library
% for usual usage
$ pip install -e .
% for development
$ pip install -e .[dev]
Official Documentation
ReadTheDocs link : https://imgann.readthedocs.io/en/latest/index.html
Usage
For functional usages in detail refer the documentation
-
To get N number of annotated images randomly. you can use coco format, pascalVOC format or csv format as annotation format. keywords can be from ['coco', 'csv', 'voc']
from imgann import Sample
Sample.show_samples( <image dataset dir> : string, <annotation file dit> : string, <number of images> : int, <annotation type> : string= 'coco', <center COCO> : bool= True )
example :
Sample.show_samples('./data/test','./annotations/test',5,'voc')
-
To convert annotation file format.
-
coco to pascal VOC format converting
from imgann import Convertor
Convertor.coco2voc( <image dataset dir> : string, <coco annotated .json file dir> : string, <voc formatted .xml file saving folder dir> : string, <center COCO> : bool= True)
\note : if
<center COCO> = True
the generating bouding box format is [X_center, Y_center, Width, Heigth]
<center COCO> = False
then 'bbox' format of .json file is [X_min, Y_min, Width, Heigth] < roboflow annotated .json files saved in this format.example :
Convertor.coco2voc('../data/train', '../data/annotations/dataset.json', '../data/annotations/voc_dataset')
-
coco to csv format converting
from imgann import Convertor
Convertor.coco2csv( <image dataset dir> : string, <coco annotated .json file dir> : string, <voc formatted .csv file dir> : string, <center COCO> : bool= True)
example :
Convertor.coco2csv('../data/train', '../data/annotations/dataset.json', '../data/annotations/dataset.csv')
-
csv to coco format converting
from imgann import Convertor
Convertor.coco2csv( <image dataset dir> : string, <csv annotated .csv file dir> : string, <coco formatted .json file dir> : string, <center COCO> : bool= True)
example :
Convertor.csv2coco('../data/train', '../data/annotations/dataset.csv', '../data/annotations/dataset.json')
-
csv to pascal VOC format converting
from imgann import Convertor
Convertor.csv2voc( <image dataset dir> : string, <csv annotated .csv file dir> : string, <pascal VOC formatted .xml file saving folder dir> : string)
example :
Convertor.coco2csv('../data/train', '../data/annotations/dataset.csv', '../data/annotations/voc_dataset')
-
pascal VOC to coco format converting
from imgann import Convertor
Convertor.voc2coco( <image dataset dir> : string, <pascal VOC annotated file included folder dir> : string, <coco formatted .json file dir> : string, <center COCO> : bool= True)
example :
Convertor.voc2coco('../data/train', '../data/annotations/voc_dataset', '../data/annotations/dataset.json)
-
pascal VOC to csv format converting
from imgann import Convertor
Convertor.voc2csv( <image dataset dir> : string, <pascal VOC annotated file included folder dir> : string, <csv formatted .csv file dir> : string)
example :
Convertor.voc2coco('../data/train', '../data/annotations/voc_dataset', '../data/annotations/dataset.csv)
-
csv to TF multi-label converting
from imgann import Convertor
Convertor.csv2multilabel( <csv dataset dir> : string, <save dir> : string)
example :
Convertor.csv2multilabel('../data/train/annotation.csv', '../data/annotations/dataset.csv)
-
-
To get summary of image dataset
from imgann import Sample
Sample.describe_data( <path to image dataset main folder> )
example :
Sample.describe_data('../data/train')
-
To get summary of complete data annotation
from imgann import Sample
Sample.describe_ann( <path to image dataset main folder> , <path to image annotation file/folder> , <image annotation type>['coco', 'yolo', 'csv', 'voc'], <center COCO> : bool= True)
example :
Sample.describe_ann('../data/train', '../data/annotations/dataset.json', 'coco')
ImgAnn
Copyright © 2022 @nipdep
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