coco-toolkit 0.1.0

Introduction

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.

System requirements

Installation

Basic usage

1 - Import

1.1 -Import preprocess

from coco_toolkit.helper.preprocess import PreProcess

1.2 -Import merge

from coco_toolkit.helper.merge import merge_multiple_cocos

1.2 -Import report

from coco_toolkit.helper.report import AnalyzeCategories

2 - Sample usage

2.1 - Usage filter class

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")

Check before PR

black . --config pyproject.toml
isort .
pre-commit run --all-files