├── .github ├── FUNDING.yml └── workflows │ ├── ci.yml │ ├── package_testing.yml │ └── pypi.yml ├── .gitignore ├── LICENSE ├── README.md ├── labelme2coco ├── __init__.py ├── cli.py ├── labelme2coco.py └── utils.py ├── pyproject.toml ├── requirements.txt ├── setup.cfg ├── setup.py └── tests ├── __init__.py ├── data ├── coco_false_0.json ├── coco_false_1.json ├── coco_false_10.json ├── coco_false_11.json ├── coco_false_12.json ├── coco_false_13.json ├── coco_false_14.json ├── coco_false_15.json ├── coco_false_16.json ├── coco_false_2.json ├── coco_false_3.json ├── coco_false_4.json ├── coco_false_5.json ├── coco_false_6.json ├── coco_false_7.json ├── coco_false_8.json ├── coco_false_9.json ├── coco_true_0.json ├── coco_true_1.json └── labelme_annot │ ├── 2011_000025.jpg │ └── 2011_000025.json └── test_unit.py /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | github: fcakyon 2 | -------------------------------------------------------------------------------- /.github/workflows/ci.yml: -------------------------------------------------------------------------------- 1 | name: CI 2 | 3 | on: 4 | push: 5 | branches: [ master ] 6 | pull_request: 7 | branches: [ master ] 8 | 9 | jobs: 10 | build: 11 | 12 | runs-on: ubuntu-latest 13 | strategy: 14 | matrix: 15 | operating-system: [ubuntu-latest, windows-latest, macos-latest] 16 | python-version: [3.7, 3.8, 3.9, "3.10"] 17 | fail-fast: false 18 | 19 | steps: 20 | - name: Checkout 21 | uses: actions/checkout@v2 22 | - name: Set up Python 23 | uses: actions/setup-python@v2 24 | with: 25 | python-version: ${{ matrix.python-version }} 26 | - name: Restore Ubuntu cache 27 | uses: actions/cache@v1 28 | if: matrix.operating-system == 'ubuntu-latest' 29 | with: 30 | path: ~/.cache/pip 31 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 32 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 33 | - name: Restore MacOS cache 34 | uses: actions/cache@v1 35 | if: matrix.operating-system == 'macos-latest' 36 | with: 37 | path: ~/Library/Caches/pip 38 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 39 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 40 | - name: Restore Windows cache 41 | uses: actions/cache@v1 42 | if: matrix.operating-system == 'windows-latest' 43 | with: 44 | path: ~\AppData\Local\pip\Cache 45 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 46 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 47 | - name: Update pip 48 | run: python -m pip install --upgrade pip 49 | - name: Install dependencies 50 | run: | 51 | python -m pip install --upgrade pip 52 | pip install -r requirements.txt 53 | - name: Lint with flake8 54 | run: | 55 | pip install flake8 56 | # stop the build if there are Python syntax errors or undefined names 57 | flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics 58 | # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide 59 | flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics 60 | - name: Test with unittest 61 | run: | 62 | python -m unittest 63 | - name: Test CLI 64 | run: | 65 | pip install . 66 | labelme2coco tests/data/labelme_annot --train_split_rate 0.85 67 | -------------------------------------------------------------------------------- /.github/workflows/package_testing.yml: -------------------------------------------------------------------------------- 1 | name: Package Testing 2 | 3 | on: 4 | schedule: 5 | - cron: '0 0 * * *' # Runs at 00:00 UTC every day 6 | 7 | jobs: 8 | build: 9 | runs-on: ubuntu-latest 10 | 11 | strategy: 12 | matrix: 13 | operating-system: [ubuntu-latest, windows-latest, macos-latest] 14 | python-version: [3.7, 3.8, 3.9, "3.10"] 15 | fail-fast: false 16 | 17 | steps: 18 | - name: Checkout 19 | uses: actions/checkout@v2 20 | 21 | - name: Set up Python 22 | uses: actions/setup-python@v2 23 | with: 24 | python-version: ${{ matrix.python-version }} 25 | 26 | - name: Restore Ubuntu cache 27 | uses: actions/cache@v1 28 | if: matrix.operating-system == 'ubuntu-latest' 29 | with: 30 | path: ~/.cache/pip 31 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 32 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 33 | 34 | - name: Restore MacOS cache 35 | uses: actions/cache@v1 36 | if: matrix.operating-system == 'macos-latest' 37 | with: 38 | path: ~/Library/Caches/pip 39 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 40 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 41 | 42 | - name: Restore Windows cache 43 | uses: actions/cache@v1 44 | if: matrix.operating-system == 'windows-latest' 45 | with: 46 | path: ~\AppData\Local\pip\Cache 47 | key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}} 48 | restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}- 49 | 50 | - name: Update pip 51 | run: python -m pip install --upgrade pip 52 | 53 | - name: Install latest labelme2coco package 54 | run: > 55 | pip install --upgrade --force-reinstall labelme2coco 56 | 57 | - name: Test with unittest 58 | run: | 59 | pip install pytest 60 | python -m unittest 61 | 62 | - name: Test CLI 63 | run: | 64 | pip install . 65 | labelme2coco tests/data/labelme_annot --train_split_rate 0.85 -------------------------------------------------------------------------------- /.github/workflows/pypi.yml: -------------------------------------------------------------------------------- 1 | name: Upload Python Package 2 | 3 | on: 4 | release: 5 | types: [created, edited] 6 | 7 | jobs: 8 | deploy: 9 | 10 | runs-on: ubuntu-latest 11 | 12 | steps: 13 | - uses: actions/checkout@v2 14 | - name: Set up Python 15 | uses: actions/setup-python@v2 16 | with: 17 | python-version: '3.x' 18 | - name: Install dependencies 19 | run: | 20 | python -m pip install --upgrade pip 21 | pip install setuptools wheel twine 22 | - name: Build and publish 23 | env: 24 | TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }} 25 | TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }} 26 | run: | 27 | python setup.py sdist bdist_wheel 28 | twine upload dist/* 29 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # ide 10 | .vscode 11 | 12 | # Distribution / packaging 13 | .Python 14 | build/ 15 | develop-eggs/ 16 | dist/ 17 | downloads/ 18 | eggs/ 19 | .eggs/ 20 | lib/ 21 | lib64/ 22 | parts/ 23 | sdist/ 24 | var/ 25 | wheels/ 26 | pip-wheel-metadata/ 27 | share/python-wheels/ 28 | *.egg-info/ 29 | .installed.cfg 30 | *.egg 31 | MANIFEST 32 | 33 | # PyInstaller 34 | # Usually these files are written by a python script from a template 35 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 36 | *.manifest 37 | *.spec 38 | 39 | # Installer logs 40 | pip-log.txt 41 | pip-delete-this-directory.txt 42 | 43 | # Unit test / coverage reports 44 | htmlcov/ 45 | .tox/ 46 | .nox/ 47 | .coverage 48 | .coverage.* 49 | .cache 50 | nosetests.xml 51 | coverage.xml 52 | *.cover 53 | *.py,cover 54 | .hypothesis/ 55 | .pytest_cache/ 56 | 57 | # Translations 58 | *.mo 59 | *.pot 60 | 61 | # Django stuff: 62 | *.log 63 | local_settings.py 64 | db.sqlite3 65 | db.sqlite3-journal 66 | 67 | # Flask stuff: 68 | instance/ 69 | .webassets-cache 70 | 71 | # Scrapy stuff: 72 | .scrapy 73 | 74 | # Sphinx documentation 75 | docs/_build/ 76 | 77 | # PyBuilder 78 | target/ 79 | 80 | # Jupyter Notebook 81 | .ipynb_checkpoints 82 | 83 | # IPython 84 | profile_default/ 85 | ipython_config.py 86 | 87 | # pyenv 88 | .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 98 | __pypackages__/ 99 | 100 | # Celery stuff 101 | celerybeat-schedule 102 | celerybeat.pid 103 | 104 | # SageMath parsed files 105 | *.sage.py 106 | 107 | # Environments 108 | .env 109 | .venv 110 | env/ 111 | venv/ 112 | ENV/ 113 | env.bak/ 114 | venv.bak/ 115 | 116 | # Spyder project settings 117 | .spyderproject 118 | .spyproject 119 | 120 | # Rope project settings 121 | .ropeproject 122 | 123 | # mkdocs documentation 124 | /site 125 | 126 | # mypy 127 | .mypy_cache/ 128 | .dmypy.json 129 | dmypy.json 130 | 131 | # Pyre type checker 132 | .pyre/ 133 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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2 |

3 | labelme2coco 4 |

5 | 6 | downloads 7 | pypi version 8 | ci 9 | fcakyon twitter 10 | 11 |

12 | A lightweight package for converting your labelme annotations into COCO object detection format. 13 |

14 | 15 |

16 | teaser 17 |

18 |
19 | 20 | ## Convert LabelMe annotations to COCO format in one step 21 | [labelme](https://github.com/wkentaro/labelme) is a widely used is a graphical image annotation tool that supports classification, segmentation, instance segmentation and object detection formats. 22 | However, widely used frameworks/models such as Yolact/Solo, Detectron, MMDetection etc. requires COCO formatted annotations. 23 | 24 | You can use this package to convert labelme annotations to COCO format. 25 | 26 | ## Getting started 27 | ### Installation 28 | ``` 29 | pip install -U labelme2coco 30 | ``` 31 | 32 | ### Basic Usage 33 | 34 | ```python 35 | labelme2coco path/to/labelme/dir 36 | ``` 37 | 38 | ```python 39 | labelme2coco path/to/labelme/dir --train_split_rate 0.85 40 | ``` 41 | 42 | ```python 43 | labelme2coco path/to/labelme/dir --category_id_start 1 44 | ``` 45 | 46 | ### Advanced Usage 47 | 48 | ```python 49 | # import package 50 | import labelme2coco 51 | 52 | # set directory that contains labelme annotations and image files 53 | labelme_folder = "tests/data/labelme_annot" 54 | 55 | # set export dir 56 | export_dir = "tests/data/" 57 | 58 | # set train split rate 59 | train_split_rate = 0.85 60 | 61 | # set category ID start value 62 | category_id_start = 1 63 | 64 | # convert labelme annotations to coco 65 | labelme2coco.convert(labelme_folder, export_dir, train_split_rate, category_id_start=category_id_start) 66 | ``` 67 | 68 | ```python 69 | # import functions 70 | from labelme2coco import get_coco_from_labelme_folder, save_json 71 | 72 | # set labelme training data directory 73 | labelme_train_folder = "tests/data/labelme_annot" 74 | 75 | # set labelme validation data directory 76 | labelme_val_folder = "tests/data/labelme_annot" 77 | 78 | # set path for coco json to be saved 79 | export_dir = "tests/data/" 80 | 81 | # set category ID start value 82 | category_id_start = 1 83 | 84 | # create train coco object 85 | train_coco = get_coco_from_labelme_folder(labelme_train_folder, category_id_start=category_id_start) 86 | 87 | # export train coco json 88 | save_json(train_coco.json, export_dir+"train.json") 89 | 90 | # create val coco object 91 | val_coco = get_coco_from_labelme_folder(labelme_val_folder, coco_category_list=train_coco.json_categories, category_id_start=category_id_start) 92 | 93 | # export val coco json 94 | save_json(val_coco.json, export_dir+"val.json") 95 | ``` 96 | -------------------------------------------------------------------------------- /labelme2coco/__init__.py: -------------------------------------------------------------------------------- 1 | from __future__ import absolute_import 2 | 3 | __version__ = "0.2.6" 4 | 5 | import logging 6 | import os 7 | from pathlib import Path 8 | 9 | from sahi.utils.file import save_json 10 | 11 | from labelme2coco.labelme2coco import get_coco_from_labelme_folder 12 | 13 | from typing import List 14 | 15 | logger = logging.getLogger(__name__) 16 | logging.basicConfig( 17 | format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", 18 | datefmt="%m/%d/%Y %H:%M:%S", 19 | level=os.environ.get("LOGLEVEL", "INFO").upper(), 20 | ) 21 | 22 | 23 | def convert( 24 | labelme_folder: str, 25 | export_dir: str = "runs/labelme2coco/", 26 | train_split_rate: float = 1, 27 | skip_labels: List[str] = [], 28 | category_id_start: int = 0, 29 | ): 30 | """ 31 | Args: 32 | labelme_folder: folder that contains labelme annotations and image files 33 | export_dir: path for coco jsons to be exported 34 | train_split_rate: ration fo train split 35 | category_id_start: starting value for category IDs (default: 0) 36 | """ 37 | coco = get_coco_from_labelme_folder(labelme_folder, skip_labels=skip_labels, category_id_start=category_id_start) 38 | if train_split_rate < 1: 39 | result = coco.split_coco_as_train_val(train_split_rate) 40 | # export train split 41 | save_path = str(Path(export_dir) / "train.json") 42 | save_json(result["train_coco"].json, save_path) 43 | logger.info(f"Training split in COCO format is exported to {save_path}") 44 | # export val split 45 | save_path = str(Path(export_dir) / "val.json") 46 | save_json(result["val_coco"].json, save_path) 47 | logger.info(f"Validation split in COCO format is exported to {save_path}") 48 | else: 49 | save_path = str(Path(export_dir) / "dataset.json") 50 | save_json(coco.json, save_path) 51 | logger.info(f"Converted annotations in COCO format is exported to {save_path}") 52 | -------------------------------------------------------------------------------- /labelme2coco/cli.py: -------------------------------------------------------------------------------- 1 | import fire 2 | 3 | from labelme2coco import convert 4 | 5 | 6 | def app() -> None: 7 | """Cli app.""" 8 | fire.Fire(convert) 9 | 10 | 11 | if __name__ == "__main__": 12 | app() 13 | -------------------------------------------------------------------------------- /labelme2coco/labelme2coco.py: -------------------------------------------------------------------------------- 1 | from pathlib import Path 2 | from typing import List 3 | 4 | import numpy as np 5 | from sahi.utils.coco import Coco, CocoAnnotation, CocoCategory, CocoImage 6 | from sahi.utils.file import list_files_recursively, load_json, save_json 7 | from tqdm import tqdm 8 | 9 | 10 | class labelme2coco: 11 | def __init__(self): 12 | raise RuntimeError( 13 | "Use labelme2coco.convert() or labelme2coco.get_coco_from_labelme_folder() instead." 14 | ) 15 | 16 | 17 | def get_coco_from_labelme_folder( 18 | labelme_folder: str, coco_category_list: List = None, skip_labels: List[str] = [], category_id_start: int = 0 19 | ) -> Coco: 20 | """ 21 | Args: 22 | labelme_folder: folder that contains labelme annotations and image files 23 | coco_category_list: start from a predefined coco cateory list 24 | """ 25 | # get json list 26 | _, abs_json_path_list = list_files_recursively(labelme_folder, contains=[".json"]) 27 | labelme_json_list = abs_json_path_list 28 | labelme_json_list.sort() 29 | 30 | # init coco object 31 | coco = Coco() 32 | 33 | if coco_category_list is not None: 34 | coco.add_categories_from_coco_category_list(coco_category_list) 35 | 36 | if len(skip_labels) > 0: 37 | print(f"Will skip the following annotated labels: {skip_labels}") 38 | 39 | # parse labelme annotations 40 | # depending on cli arguments, will start counting at 1 41 | category_ind = category_id_start 42 | for json_path in tqdm( 43 | labelme_json_list, "Converting labelme annotations to COCO format" 44 | ): 45 | # Taken from https://github.com/fcakyon/labelme2coco/pull/17 46 | data = load_json(json_path) 47 | # get image size 48 | image_path = str(Path(json_path).parent / data["imagePath"]) 49 | # use the image sizes provided by labelme (they already account for 50 | # things such as EXIF orientation) 51 | width = data["imageWidth"] 52 | height = data["imageHeight"] 53 | # init coco image 54 | coco_image = CocoImage(file_name=image_path, height=height, width=width) 55 | # iterate over annotations 56 | for shape in data["shapes"]: 57 | # set category name and id 58 | category_name = shape["label"] 59 | if category_name in skip_labels: 60 | continue 61 | category_id = None 62 | for ( 63 | coco_category_id, 64 | coco_category_name, 65 | ) in coco.category_mapping.items(): 66 | if category_name == coco_category_name: 67 | category_id = coco_category_id 68 | break 69 | # add category if not present 70 | if category_id is None: 71 | category_id = category_ind 72 | coco.add_category(CocoCategory(id=category_id, name=category_name)) 73 | category_ind += 1 74 | 75 | # convert circles, lines, and points to bbox/segmentation 76 | if shape["shape_type"] == "circle": 77 | (cx, cy), (x1, y1) = shape["points"] 78 | r = np.linalg.norm(np.array([x1 - cx, y1 - cy])) 79 | angles = np.linspace(0, 2 * np.pi, 50 * (int(r) + 1)) 80 | x = cx + r * np.cos(angles) 81 | y = cy + r * np.sin(angles) 82 | points = np.rint(np.append(x, y).reshape(-1, 2, order='F')) 83 | _, index = np.unique(points, return_index=True, axis=0) 84 | shape["points"] = points[np.sort(index)] 85 | shape["shape_type"] = "polygon" 86 | elif shape["shape_type"] == "line": 87 | (x1, y1), (x2, y2) = shape["points"] 88 | shape["points"] = [x1, y1, x2, y2, x2 + 1e-3, y2 + 1e-3, x1 + 1e-3, y1 + 1e-3] 89 | shape["shape_type"] = "polygon" 90 | elif shape["shape_type"] == "point": 91 | (x1, y1) = shape["points"][0] 92 | shape["points"] = [[x1, y1], [x1 + 1, y1 + 1]] 93 | shape["shape_type"] = "rectangle" 94 | 95 | # parse bbox/segmentation 96 | if shape["shape_type"] == "rectangle": 97 | x1 = shape["points"][0][0] 98 | y1 = shape["points"][0][1] 99 | x2 = shape["points"][1][0] 100 | y2 = shape["points"][1][1] 101 | coco_annotation = CocoAnnotation( 102 | bbox=[x1, y1, x2 - x1, y2 - y1], 103 | category_id=category_id, 104 | category_name=category_name, 105 | ) 106 | elif shape["shape_type"] == "polygon": 107 | segmentation = [np.asarray(shape["points"]).flatten().tolist()] 108 | coco_annotation = CocoAnnotation( 109 | segmentation=segmentation, 110 | category_id=category_id, 111 | category_name=category_name, 112 | ) 113 | else: 114 | raise NotImplementedError( 115 | f'shape_type={shape["shape_type"]} not supported.' 116 | ) 117 | coco_image.add_annotation(coco_annotation) 118 | coco.add_image(coco_image) 119 | 120 | return coco 121 | 122 | 123 | if __name__ == "__main__": 124 | labelme_folder = "tests/data/labelme_annot" 125 | coco = get_coco_from_labelme_folder(labelme_folder) -------------------------------------------------------------------------------- /labelme2coco/utils.py: -------------------------------------------------------------------------------- 1 | import json 2 | import os 3 | 4 | import jsonschema 5 | 6 | image_schema = { 7 | "type": "object", 8 | "properties": {"file_name": {"type": "string"}, "id": {"type": "integer"}}, 9 | "required": ["file_name", "id"], 10 | } 11 | 12 | segmentation_schema = { 13 | "type": "array", 14 | "items": { 15 | "type": "array", 16 | "items": { 17 | "type": "number", 18 | }, 19 | "additionalItems": False, 20 | }, 21 | "additionalItems": False, 22 | } 23 | 24 | annotation_schema = { 25 | "type": "object", 26 | "properties": { 27 | "image_id": {"type": "integer"}, 28 | "category_id": {"type": "integer"}, 29 | "segmentation": segmentation_schema, 30 | }, 31 | "required": ["image_id", "category_id", "segmentation"], 32 | } 33 | 34 | category_schema = { 35 | "type": "object", 36 | "properties": {"name": {"type": "string"}, "id": {"type": "integer"}}, 37 | "required": ["name", "id"], 38 | } 39 | 40 | coco_schema = { 41 | "type": "object", 42 | "properties": { 43 | "images": {"type": "array", "items": image_schema, "additionalItems": False}, 44 | "annotations": { 45 | "type": "array", 46 | "items": annotation_schema, 47 | "additionalItems": False, 48 | }, 49 | "categories": { 50 | "type": "array", 51 | "items": category_schema, 52 | "additionalItems": False, 53 | }, 54 | }, 55 | "required": ["images", "annotations", "categories"], 56 | } 57 | 58 | 59 | def read_and_validate_coco_annotation(coco_annotation_path: str) -> (dict, bool): 60 | """ 61 | Reads coco formatted annotation file and validates its fields. 62 | """ 63 | try: 64 | with open(coco_annotation_path) as json_file: 65 | coco_dict = json.load(json_file) 66 | jsonschema.validate(coco_dict, coco_schema) 67 | response = True 68 | except jsonschema.exceptions.ValidationError as e: 69 | print("well-formed but invalid JSON:", e) 70 | response = False 71 | except json.decoder.JSONDecodeError as e: 72 | print("poorly-formed text, not JSON:", e) 73 | response = False 74 | 75 | return coco_dict, response 76 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.black] 2 | line-length = 90 3 | 4 | [tool.isort] 5 | line_length = 90 6 | profile = "black" -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | sahi>=0.8.19 2 | jsonschema>=2.6.0 -------------------------------------------------------------------------------- /setup.cfg: -------------------------------------------------------------------------------- 1 | [flake8] 2 | max-line-length = 90 3 | exclude =.git,__pycache__,docs/source/conf.py,build,dist 4 | ignore = I101,I201,F401,F403,S001,D100,D101,D102,D103,D104,D105,D106,D107,D200,D205,D400,W504,D202,E203,E722,W503,B006 5 | inline-quotes = " 6 | 7 | [mypy] 8 | ignore_missing_imports = True 9 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | import io 2 | import os 3 | import re 4 | 5 | import setuptools 6 | 7 | 8 | def get_long_description(): 9 | base_dir = os.path.abspath(os.path.dirname(__file__)) 10 | with io.open(os.path.join(base_dir, "README.md"), encoding="utf-8") as f: 11 | return f.read() 12 | 13 | 14 | def get_requirements(): 15 | with open("requirements.txt") as f: 16 | return f.read().splitlines() 17 | 18 | 19 | def get_version(): 20 | current_dir = os.path.abspath(os.path.dirname(__file__)) 21 | version_file = os.path.join(current_dir, "labelme2coco", "__init__.py") 22 | with io.open(version_file, encoding="utf-8") as f: 23 | return re.search(r'^__version__ = [\'"]([^\'"]*)[\'"]', f.read(), re.M).group(1) 24 | 25 | 26 | setuptools.setup( 27 | name="labelme2coco", 28 | version=get_version(), 29 | author="Fatih Cagatay Akyon", 30 | author_email="", 31 | description="Convert labelme annotations into coco format in one step", 32 | long_description=get_long_description(), 33 | long_description_content_type="text/markdown", 34 | url="https://github.com/fcakyon/labelme2coco", 35 | packages=setuptools.find_packages(), 36 | classifiers=[ 37 | "Programming Language :: Python :: 3", 38 | "License :: OSI Approved :: MIT License", 39 | "Operating System :: OS Independent", 40 | ], 41 | install_requires=get_requirements(), 42 | python_requires=">=3.7", 43 | entry_points={ 44 | "console_scripts": [ 45 | "labelme2coco=labelme2coco.cli:app", 46 | ], 47 | }, 48 | ) 49 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fcakyon/labelme2coco/fe1cbc64eca4336bd249c475e45578ea8ce23d03/tests/__init__.py -------------------------------------------------------------------------------- /tests/data/coco_false_0.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotation": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_1.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [1.2, 2, 3, 4, 5, 6]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_10.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_11.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}]} -------------------------------------------------------------------------------- /tests/data/coco_false_12.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": {"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_13.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": {"name": "id_card", "id": 1}} -------------------------------------------------------------------------------- /tests/data/coco_false_14.json: -------------------------------------------------------------------------------- 1 | {"images": {"file_name": "data/midv500/images/example1.tif", "id": 1}, "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_15.json: -------------------------------------------------------------------------------- 1 | {"image": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_16.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categoryes": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_2.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card"}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_3.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif"}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_4.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_5.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_6.json: -------------------------------------------------------------------------------- 1 | {"images": [{"id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_7.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_8.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_false_9.json: -------------------------------------------------------------------------------- 1 | {"annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_true_0.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/midv500/images/example1.tif", "id": 1}, {"file_name": "data/midv500/images/example2.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 1, "category_id": 2, "segmentation": [[1, 2, 3, 4, 5, 6]]}, {"image_id": 2, "category_id": 1, "segmentation": [[1, 2, 3, 4, 5, 6]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/coco_true_1.json: -------------------------------------------------------------------------------- 1 | {"images": [{"file_name": "data/43_tur_id/images/CA/CA43_01.tif", "id": 1}, {"file_name": "data/43_tur_id/images/CA/CA43_01.tif", "id": 2}], "annotations": [{"image_id": 1, "category_id": 1, "segmentation": [[97, 672, 904, 643, 931, 1142, 122, 1185]]}, {"image_id": 1, "category_id": 2, "segmentation": [[97, 500, 904.0, 643, 931, 1100, 122, 1185]]}, {"image_id": 2, "category_id": 1, "segmentation": [[97, 672, 904.0, 643, 931, 1142, 122, 1185]]}], "categories": [{"name": "id_card", "id": 1}, {"name": "person", "id": 2}]} -------------------------------------------------------------------------------- /tests/data/labelme_annot/2011_000025.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fcakyon/labelme2coco/fe1cbc64eca4336bd249c475e45578ea8ce23d03/tests/data/labelme_annot/2011_000025.jpg -------------------------------------------------------------------------------- /tests/data/labelme_annot/2011_000025.json: -------------------------------------------------------------------------------- 1 | { 2 | "version": "4.0.0", 3 | "flags": {}, 4 | "shapes": [ 5 | { 6 | "label": "bus", 7 | "points": [ 8 | [ 9 | 260.936170212766, 10 | 23.33306055646483 11 | ], 12 | [ 13 | 193.936170212766, 14 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| 253.33306055646483 79 | ], 80 | [ 81 | 428.936170212766, 82 | 237.33306055646483 83 | ], 84 | [ 85 | 409.936170212766, 86 | 221.33306055646483 87 | ], 88 | [ 89 | 409.936170212766, 90 | 151.33306055646483 91 | ], 92 | [ 93 | 430.936170212766, 94 | 144.33306055646483 95 | ], 96 | [ 97 | 433.936170212766, 98 | 113.33306055646483 99 | ], 100 | [ 101 | 431.936170212766, 102 | 97.33306055646483 103 | ], 104 | [ 105 | 408.936170212766, 106 | 91.33306055646483 107 | ], 108 | [ 109 | 395.936170212766, 110 | 51.33306055646483 111 | ], 112 | [ 113 | 338.936170212766, 114 | 26.33306055646483 115 | ] 116 | ], 117 | "group_id": null, 118 | "shape_type": "polygon", 119 | "flags": {} 120 | }, 121 | { 122 | "label": "bus", 123 | "points": [ 124 | [ 125 | 88.93617021276599, 126 | 115.56382978723406 127 | ], 128 | [ 129 | 0.9361702127659877, 130 | 96.56382978723406 131 | ], 132 | [ 133 | 0.0, 134 | 251.968085106388 135 | ], 136 | [ 137 | 0.9361702127659877, 138 | 265.56382978723406 139 | ], 140 | [ 141 | 27.936170212765987, 142 | 265.56382978723406 143 | ], 144 | [ 145 | 29.936170212765987, 146 | 283.56382978723406 147 | ], 148 | [ 149 | 63.93617021276599, 150 | 281.56382978723406 151 | ], 152 | [ 153 | 89.93617021276599, 154 | 252.56382978723406 155 | ], 156 | [ 157 | 100.93617021276599, 158 | 183.56382978723406 159 | ], 160 | [ 161 | 108.93617021276599, 162 | 145.56382978723406 163 | ], 164 | [ 165 | 81.93617021276599, 166 | 151.56382978723406 167 | ] 168 | ], 169 | "group_id": null, 170 | "shape_type": "polygon", 171 | "flags": {} 172 | }, 173 | { 174 | "label": "car", 175 | "points": [ 176 | [ 177 | 413.936170212766, 178 | 168.94844517184944 179 | ], 180 | [ 181 | 497.936170212766, 182 | 168.94844517184944 183 | ], 184 | [ 185 | 497.936170212766, 186 | 256.94844517184936 187 | ], 188 | [ 189 | 431.936170212766, 190 | 258.94844517184936 191 | ], 192 | [ 193 | 430.936170212766, 194 | 236.94844517184944 195 | ], 196 | [ 197 | 408.936170212766, 198 | 218.94844517184944 199 | ] 200 | ], 201 | "group_id": null, 202 | "shape_type": "polygon", 203 | "flags": {} 204 | } 205 | ], 206 | "imagePath": "2011_000025.jpg", 207 | "imageData": null, 208 | "imageHeight": 375, 209 | "imageWidth": 500 210 | } -------------------------------------------------------------------------------- /tests/test_unit.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | 3 | 4 | class Tests(unittest.TestCase): 5 | def test_read_and_validate_coco_annotation(self): 6 | from labelme2coco.utils import read_and_validate_coco_annotation 7 | 8 | false_sample_list = [ 9 | "tests/data/coco_false_" + str(ind) + ".json" for ind in range(17) 10 | ] 11 | true_sample_list = [ 12 | "tests/data/coco_true_" + str(ind) + ".json" for ind in range(2) 13 | ] 14 | 15 | for false_sample in false_sample_list: 16 | _, response = read_and_validate_coco_annotation(false_sample) 17 | self.assertEqual(response, False) 18 | 19 | for true_sample in true_sample_list: 20 | _, response = read_and_validate_coco_annotation(true_sample) 21 | self.assertEqual(response, True) 22 | 23 | def test_lableme2coco(self): 24 | 25 | from labelme2coco.labelme2coco import get_coco_from_labelme_folder 26 | 27 | labelme_folder = "tests/data/labelme_annot" 28 | coco = get_coco_from_labelme_folder(labelme_folder) 29 | 30 | test_coco = coco.json 31 | self.assertEqual(int(test_coco["annotations"][1]["bbox"][1]), 96) 32 | self.assertEqual(test_coco["annotations"][1]["id"], 2) 33 | self.assertEqual(test_coco["annotations"][1]["category_id"], 0) 34 | self.assertEqual(int(test_coco["annotations"][1]["segmentation"][0][2]), 0) 35 | self.assertEqual(len(test_coco["annotations"]), 3) 36 | self.assertEqual(test_coco["images"][0]["height"], 375) 37 | self.assertEqual(len(test_coco["images"]), 1) 38 | self.assertEqual(test_coco["categories"][0]["name"], "bus") 39 | self.assertEqual(len(test_coco["categories"]), 2) 40 | 41 | 42 | if __name__ == "__main__": 43 | unittest.main() 44 | --------------------------------------------------------------------------------