Metadata-Version: 2.1
Name: labelme2coco
Version: 0.1.1
Summary: Convert labelme annotations into coco format in one step
Home-page: https://github.com/fcakyon/labelme2coco
Author: Fatih Cagatay Akyon
Author-email: 
License: UNKNOWN
Description: [![PyPI version](https://badge.fury.io/py/labelme2coco.svg)](https://badge.fury.io/py/labelme2coco)
        ![CI](https://github.com/fcakyon/labelme2coco/workflows/CI/badge.svg)
        
        # labelme2coco Python Package for Linux/MacOS/Windows
        Make your own dataset for object detection/instance segmentation using [labelme](https://github.com/wkentaro/labelme) and transform the format to coco json format 
        
        ## Convert LabelMe annotations to COCO format in one step
        [labelme](https://github.com/wkentaro/labelme) is a widely used is a graphical image annotation tool that supports classification, segmentation, isntance segmentation and object detection formats.
        However, widely used frameworks/models such as Yolact/Solo, Detectron, MMDetection etc. requires COCO formatted annotations.
        
        You can use this package to convert labelme annotations to COCO format.
        
        ## Getting started
        ### Installation
        ```
        pip install labelme2coco
        ```
        
        ### Usage
        ```python
        # import package
        import labelme2coco
        
        # set directory that contains labelme annotations and image files
        labelme_folder = "tests/data/labelme_annot"
        
        # set path for coco json to be saved
        save_json_path = "tests/data/test_coco.json"
        
        # conert labelme annotations to coco
        labelme2coco.convert(labelme_folder, save_json_path)
        ```
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Description-Content-Type: text/markdown
