Skip to main content

Simple command line tool to convert COCO datasets to ultralytics YOLO format.

Project description

coco-to-yolo

Simple command line tool to convert COCO object detection datasets to YOLO format.

Usage

  1. Install via pip pip install coco-to-yolo
  2. Convert COCO dataset to ultralytics YOLO format using coco_to_yolo <<coco_dir>> <<output_dir>>

By default the script assumes the coco dataset to be structured as follows:

<<coco_dir>>
├── annotations
│   └── annotations.json     # Exactly ONE annotation file in COCO json format
└── images                   # Arbitary number of images (matching the file names 
    ├── image1.jpeg          # in the annotations json file)
    ├── image2.jpeg         
    └── ...

Split generation

By default the script will split 10% of the data into a test split and not generate a validation split. The ratio of splitted test and validation data can be adapted by specifying the --test_ratio and --val_ratio arguments, e.g.

Example usage

coco_to_yolo /home/COCO_ds /home/COCO_ds --test_ratio 0.15 --val_ratio 0.1

will convert the dataset in the /home/COCO_ds to the format required by YOLO, split 15% of the data for the testing, 10% for validation, and store the resulting dataset in /home/COCO_ds

Contributions

Feel free to suggest extensions and point out mistakes by creating an issue or sending me a pull request.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

coco_to_yolo-1.0.1.tar.gz (4.7 kB view details)

Uploaded Source

Built Distribution

COCO_to_YOLO-1.0.1-py3-none-any.whl (5.3 kB view details)

Uploaded Python 3

File details

Details for the file coco_to_yolo-1.0.1.tar.gz.

File metadata

  • Download URL: coco_to_yolo-1.0.1.tar.gz
  • Upload date:
  • Size: 4.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.3

File hashes

Hashes for coco_to_yolo-1.0.1.tar.gz
Algorithm Hash digest
SHA256 46e14d8e1dcb5e386df2559627809c6a690248e3344d752fe2beb0a2fc593fd4
MD5 44d6ad0d2b6510189a9b571c34fff6f2
BLAKE2b-256 05439117608a01650e589e1663501797f1bb13b039442ad4d20568f93c8a397f

See more details on using hashes here.

File details

Details for the file COCO_to_YOLO-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for COCO_to_YOLO-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4da2df39c5b771ef08980dffc70b476b5fd9613ccb7cdf99e01f2d28076042c1
MD5 9d2a459e8f1217b08a1c7e0c7b4f05d3
BLAKE2b-256 fbabc5bb462bafc5e5f147fcb82668a58711e009357d5755c9e814c605b1869e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page