metadata
dataset_info:
features:
- name: image_id
dtype: int64
- name: image
dtype: image
- name: width
dtype: int32
- name: height
dtype: int32
- name: objects
sequence:
- name: id
dtype: int64
- name: area
dtype: int64
- name: bbox
sequence: float32
length: 4
- name: category
dtype:
class_label:
names:
'0': poker-cards
'1': 59
'2': 10 Diamonds
'3': 10 Hearts
'4': 10 Spades
'5': 10 Trefoils
'6': 2 Diamonds
'7': 2 Hearts
'8': 2 Spades
'9': 2 Trefoils
'10': 3 Diamonds
'11': 3 Hearts
'12': 3 Spades
'13': 3 Trefoils
'14': 4 Diamonds
'15': 4 Hearts
'16': 4 Spades
'17': 4 Trefoils
'18': 5 Diamonds
'19': 5 Hearts
'20': 5 Spades
'21': 5 Trefoils
'22': 6 Diamonds
'23': 6 Hearts
'24': 6 Spades
'25': 6 Trefoils
'26': 7 Diamonds
'27': 7 Hearts
'28': 7 Spades
'29': 7 Trefoils
'30': 8 Diamonds
'31': 8 Hearts
'32': 8 Spades
'33': 8 Trefoils
'34': 9 Diamonds
'35': 9 Hearts
'36': 9 Spades
'37': 9 Trefoils
'38': A Diamonds
'39': A Hearts
'40': A Spades
'41': A Trefoils
'42': J Diamonds
'43': J Hearts
'44': J Spades
'45': J Trefoils
'46': K Diamonds
'47': K Hearts
'48': K Spades
'49': K Trefoils
'50': Q Diamonds
'51': Q Hearts
'52': Q Spades
'53': Q Trefoils
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- object-detection
task_ids: []
pretty_name: poker-cards-cxcvz
tags:
- rf100
Dataset Card for poker-cards-cxcvz
** The original COCO dataset is stored at dataset.tar.gz
**
Dataset Description
- Homepage: https://universe.roboflow.com/object-detection/poker-cards-cxcvz
- Point of Contact: francesco.zuppichini@gmail.com
Dataset Summary
poker-cards-cxcvz
Supported Tasks and Leaderboards
object-detection
: The dataset can be used to train a model for Object Detection.
Languages
English
Dataset Structure
Data Instances
A data point comprises an image and its object annotations.
{
'image_id': 15,
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
'width': 964043,
'height': 640,
'objects': {
'id': [114, 115, 116, 117],
'area': [3796, 1596, 152768, 81002],
'bbox': [
[302.0, 109.0, 73.0, 52.0],
[810.0, 100.0, 57.0, 28.0],
[160.0, 31.0, 248.0, 616.0],
[741.0, 68.0, 202.0, 401.0]
],
'category': [4, 4, 0, 0]
}
}
Data Fields
image
: the image idimage
:PIL.Image.Image
object containing the image. Note that when accessing the image column:dataset[0]["image"]
the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the"image"
column, i.e.dataset[0]["image"]
should always be preferred overdataset["image"][0]
width
: the image widthheight
: the image heightobjects
: a dictionary containing bounding box metadata for the objects present on the imageid
: the annotation idarea
: the area of the bounding boxbbox
: the object's bounding box (in the coco format)category
: the object's category.
Who are the annotators?
Annotators are Roboflow users
Additional Information
Licensing Information
See original homepage https://universe.roboflow.com/object-detection/poker-cards-cxcvz
Citation Information
@misc{ poker-cards-cxcvz,
title = { poker cards cxcvz Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/object-detection/poker-cards-cxcvz } },
url = { https://universe.roboflow.com/object-detection/poker-cards-cxcvz },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2023-03-29 },
}"
Contributions
Thanks to @mariosasko for adding this dataset.