Coco-toolkit is a tool for preparing and analyzing object detection data which is coco json format in Python. Tool countains merge, preprocessing, report and converter modules.
1 - Preprocessing This class obtain preprocess functions for preparing coco json dataset.
2 - Converter This module has converters functions which are Pascal voc to coco json and coco json to tfrecords.
3 - Merge Merge module has multiple coco merge function. It merges all given coco json file and return all in one output folder.
4- Report Report module has analyze dataset functions. These functions are; return information of data set, plots data set information as pie chart, and integrates data set with coco viewer.
from coco_toolkit.helper.preprocess import PreProcess
from coco_toolkit.helper.merge import merge_multiple_cocos
from coco_toolkit.helper.report import AnalyzeCategories
This function filter given class names. It returns filtered coco json as dictionary and saves filtered coco json file and filtered images in new folder.
PreProcess(path).export_according2_class(coco, categories, image_path)
parameter path : This parameter is directory of output.Function saves filtered dataset in this path.
parameter coco : Coco json file as read dictionary
parameter categories : List of to be filtered class names
parameter image_path: Dataset images folder path
coco = PreProcess(path to coco json file).reader()
PreProcess(path).export_according2_class(coco, ["human", "car"], "/home/user/data/images")
black . --config pyproject.toml
isort .
pre-commit run --all-files