{"id":15890345,"url":"https://github.com/odancona/bboxconverter","last_synced_at":"2025-12-29T18:24:54.384Z","repository":{"id":128599540,"uuid":"596106992","full_name":"ODAncona/bboxconverter","owner":"ODAncona","description":"This library allows reading and converting bounding box annotations in many popular formats ","archived":false,"fork":false,"pushed_at":"2023-06-09T21:44:56.000Z","size":40672,"stargazers_count":22,"open_issues_count":1,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-10-22T19:48:15.258Z","etag":null,"topics":["bounding-boxes","computer-vision","image-recognition","numpy","object-detection","pandas","python","pytorch","tensorflow","train-test-split"],"latest_commit_sha":null,"homepage":"https://bboxconverter.readthedocs.io/en/latest/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ODAncona.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-02-01T13:36:02.000Z","updated_at":"2024-08-26T10:16:40.000Z","dependencies_parsed_at":"2024-01-08T22:56:35.839Z","dependency_job_id":null,"html_url":"https://github.com/ODAncona/bboxconverter","commit_stats":null,"previous_names":["odancona/bbox-tools"],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ODAncona%2Fbboxconverter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ODAncona%2Fbboxconverter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ODAncona%2Fbboxconverter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ODAncona%2Fbboxconverter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ODAncona","download_url":"https://codeload.github.com/ODAncona/bboxconverter/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":221753027,"owners_count":16875073,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bounding-boxes","computer-vision","image-recognition","numpy","object-detection","pandas","python","pytorch","tensorflow","train-test-split"],"created_at":"2024-10-06T07:05:18.077Z","updated_at":"2025-12-29T18:24:54.352Z","avatar_url":"https://github.com/ODAncona.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"https://raw.githubusercontent.com/ODAncona/bboxconverter/main/docs/_static/logo.svg\" alt=\"bbox logo\" style=\"display: block; margin-left:auto; margin-right:auto;\"\u003e\u003c/img\u003e\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://pypi.org/project/bboxconverter\"\u003e\n        \u003cimg src=\"https://img.shields.io/pypi/v/bboxconverter?color=blue\" alt=\"Python versions\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pepy.tech/project/bboxconverter\"\u003e\n        \u003cimg src=\"https://pepy.tech/badge/bboxconverter\" alt=\"Total downloads\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/bboxconverter\"\u003e\n        \u003cimg src=\"https://img.shields.io/pypi/dm/bboxconverter?color=blue\" alt=\"Monthly downloads\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/bboxconverter\"\u003e\n        \u003cimg src=\"https://img.shields.io/pypi/pyversions/bboxconverter\" alt=\"Python versions\"\u003e\n    \u003c/a\u003e\n    \u003c/br\u003e\n    \u003ca href='https://github.com/ODAncona/bboxconverter/'\u003e\n        \u003cimg src='https://github.com/ODAncona/bboxconverter/actions/workflows/ci.yml/badge.svg'\u003e\n    \u003c/a\u003e\n    \u003ca href='https://bboxconverter.readthedocs.io/en/latest/?badge=latest'\u003e\n        \u003cimg src='https://readthedocs.org/projects/bboxconverter/badge/?version=latest' alt='Documentation Status'/\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://codecov.io/gh/ODAncona/bboxconverter\" \u003e \n        \u003cimg src=\"https://codecov.io/gh/ODAncona/bboxconverter/branch/main/graph/badge.svg?token=BXGO9JZYWM\"/\u003e \n    \u003c/a\u003e\n\u003c/p\u003e\n\n# bboxconverter\n\nbboxconverter is a Python library that enables seamless conversion of bounding box formats between various types and file formats. It provides an easy-to-use syntax for reading and exporting bounding box files.\n\n## Introduction\n\n### What is a bounding box?\n\nBounding boxes are a crucial component of object detection algorithms, which are used to identify and classify objects within an image or video. A bounding box is a rectangle that surrounds an object of interest in the image, and is typically represented by a set of coordinates that define the box's position and size.\n\n\u003cimg src=\"https://raw.githubusercontent.com/ODAncona/bboxconverter/main/docs/_static/bbox.png\" alt=\"Bounding box example\" style=\"display: block; margin-left:auto; margin-right:auto;\"\u003e\u003c/img\u003e\n\n### Various types and format\n\nWhen you work with bounding box you have severals things to consider.\n\nThe bounding box could be stored in **different types** like:\n\n- Top-Left Bottom-Right (TLBR), (x_min, y_min, x_max, y_max)\n- Top-Left Width Height (TLWH), (x_min, y_min, width, height)\n- Center Width Height (CWH), (x_center, y_center, width, height)\n\nWhich are popular among **different formats** like :\n\n- [COCO](\u003c(http://cocodataset.org/)\u003e) (Common Objects in Context)\n- [Pascal VOC](\u003c(http://host.robots.ox.ac.uk/pascal/VOC/)\u003e) (Visual Object Classes)\n- [YOLO](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#yolo) (You Only Look Once)\n\nFurthermore, the bounding box could be stored in **different file formats** like:\n\n- csv\n- xml\n- json\n- manifest\n- parquet\n- pickle\n\n## Installation\n\n```bash\npip install bboxconverter\n```\n\nor\n\n```bash\ngit clone https://github.com/ODAncona/bboxconverter.git\ncd bboxconverter\npoetry install\n```\n\nSee the [installation](https://bboxconverter.readthedocs.io/en/latest/guides/installation.html) guide for more informations.\n\n## Usage\n\nThe goal of this library is to seamlessly convert bounding box format using easy syntax.\n\nIt should be a breeze like...\n\n```python\nimport bboxconverter as bc\n\n# Input file path\ninput_path = './examples/example.csv'\n\n# Output file path\noutput_path = './examples/output/example.json'\n\n# Mapping between the input file and the bboxconverter format\nbbox_map = dict(\n    class_name='class',\n    file_path='name',\n    x_min='top_left_x',\n    y_min='top_left_y',\n    width='w',\n    height='h',\n    image_width='img_size_x',\n    image_height='img_size_y',\n)\n\n# Read the input file\nparser = bc.read_csv(input_path, mapping=bbox_map)\n\n# Export the file to the desired format\nparser.export(output_path=output_path, format='coco')\nparser.export(output_path=output_path, format='voc')\nparser.export(output_path=output_path, format='yolo')\n```\n\n## Documentation\n\nYou can find the documention online at [bboxconvert.readthedoc.io](https://bboxconverter.readthedocs.io/en/latest/index.html)\n\n## Changelog\n\nSee the [CHANGELOG](https://github.com/ODAncona/bboxconverter/blob/main/CHANGELOG.md) file for details.\n\n## Contributing\n\nContributions are welcome! Please read the [contributing guidelines](https://github.com/ODAncona/bboxconverter/blob/main/CONTRIBUTING.md) first.\n\n## License\n\nThis project is licensed under the GPLV3 License - see the [LICENSE](https://github.com/ODAncona/bboxconverter/blob/main/LICENSE) file for details.\n\n## Acknowledgments\n\n- [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC/)\n- [COCO](http://cocodataset.org/#home)\n- [YOLO](https://pjreddie.com/darknet/yolo/)\n- [Albumentation](https://albumentations.ai/)\n- [Pyodi](https://github.com/Gradiant/pyodi)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fodancona%2Fbboxconverter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fodancona%2Fbboxconverter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fodancona%2Fbboxconverter/lists"}