README.md

metadata

license: cc-by-4.0
size_categories:
  - n<1K
task_categories:
  - object-detection
language:
  - en
pretty_name: COCO Keypoints

Dataset Card for "COCO Keypoints"

Quick Start

Usage

>>> from datasets.load import load_dataset

>>> dataset = load_dataset('whyen-wang/coco_keypoints')
>>> example = dataset['train'][0]
>>> print(example)
{'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x360>,
 'bboxes': [
   [339.8800048828125, 22.15999984741211,
    153.8800048828125, 300.7300109863281],
   [471.6400146484375, 172.82000732421875,
    35.91999816894531, 48.099998474121094]],
 'keypoints': [[
    [368, 61, 1], [369, 52, 2], [0, 0, 0], [382, 48, 2], [0, 0, 0],
    [368, 84, 2], [435, 81, 2], [362, 125, 2], [446, 125, 2], [360, 153, 2],
    [0, 0, 0], [397, 167, 1], [439, 166, 1], [369, 193, 2], [461, 234, 2],
    [361, 246, 2], [474, 287, 2]
   ], [[...]]
 ]}

Visualization

>>> import cv2
>>> import numpy as np
>>> from PIL import Image

>>> def visualize(example):
        image = np.array(example['image'])
        bboxes = np.array(example['bboxes']).round().astype(int)
        bboxes[:, 2:] += bboxes[:, :2]
        keypoints = example['keypoints']
        n = len(bboxes)
        for i in range(n):
            color = (255, 0, 0)
            cv2.rectangle(image, bboxes[i, :2], bboxes[i, 2:], color, 2)
            ks = keypoints[i]
            for k in ks:
                if k[-1] == 2:
                    cv2.circle(
                        image, k[:2], 5, (0, 255, 0), 1
                    )
        return image

>>> Image.fromarray(visualize(example))

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://cocodataset.org/
• Repository: None
• Paper: Microsoft COCO: Common Objects in Context
• Leaderboard: Papers with Code
• Point of Contact: None

Dataset Summary

COCO is a large-scale object detection, segmentation, and captioning dataset.

Supported Tasks and Leaderboards

Object Detection

Languages

en

Dataset Structure

Data Instances

An example looks as follows.

{
    "image": PIL.Image(mode="RGB"),
    "bboxes": [
        [339.8800048828125, 22.15999984741211,
            153.8800048828125, 300.7300109863281],
        [471.6400146484375, 172.82000732421875,
            35.91999816894531, 48.099998474121094]],
    "keypoints": [[
        [368, 61, 1], [369, 52, 2], [0, 0, 0], [382, 48, 2], [0, 0, 0],
        [368, 84, 2], [435, 81, 2], [362, 125, 2], [446, 125, 2], [360, 153, 2],
        [0, 0, 0], [397, 167, 1], [439, 166, 1], [369, 193, 2], [461, 234, 2],
        [361, 246, 2], [474, 287, 2]
      ], [[...]]
    ]
}

Data Fields

[More Information Needed]

Data Splits

name	train	validation
default	64,115	2,693

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Creative Commons Attribution 4.0 License

Citation Information

@article{cocodataset,
  author    = {Tsung{-}Yi Lin and Michael Maire and Serge J. Belongie and Lubomir D. Bourdev and Ross B. Girshick and James Hays and Pietro Perona and Deva Ramanan and Piotr Doll{'{a} }r and C. Lawrence Zitnick},
  title     = {Microsoft {COCO:} Common Objects in Context},
  journal   = {CoRR},
  volume    = {abs/1405.0312},
  year      = {2014},
  url       = {http://arxiv.org/abs/1405.0312},
  archivePrefix = {arXiv},
  eprint    = {1405.0312},
  timestamp = {Mon, 13 Aug 2018 16:48:13 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/LinMBHPRDZ14},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Contributions

Thanks to @github-whyen-wang for adding this dataset.