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---
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': characters
'1': Akali
'2': Blitzcrank
'3': Braum
'4': Caitlyn
'5': Camille
'6': Cho-Gath
'7': Darius
'8': Dr- Mundo
'9': Ekko
'10': Ezreal
'11': Fiora
'12': Galio
'13': Gankplank
'14': Garen
'15': Graves
'16': Heimerdinger
'17': Illaoi
'18': Janna
'19': Jayce
'20': Jhin
'21': Jinx
'22': Kai-Sa
'23': Kassadin
'24': Katarina
'25': Kog-Maw
'26': Leona
'27': Lissandra
'28': Lulu
'29': Lux
'30': Malzahar
'31': Miss Fortune
'32': Orianna
'33': Poppy
'34': Quinn
'35': Samira
'36': Seraphine
'37': Shaco
'38': Singed
'39': Sion
'40': Swain
'41': Tahm Kench
'42': Talon
'43': Taric
'44': Tristana
'45': Trundle
'46': Twisted Fate
'47': Twitch
'48': Urgot
'49': Veigar
'50': Vex
'51': Vi
'52': Viktor
'53': Warwick
'54': Yone
'55': Yuumi
'56': Zac
'57': Ziggs
'58': Zilean
'59': Zyra
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: team-fight-tactics
tags:
- rf100
---
# Dataset Card for team-fight-tactics
** The original COCO dataset is stored at `dataset.tar.gz`**
## Dataset Description
- **Homepage:** https://universe.roboflow.com/object-detection/team-fight-tactics
- **Point of Contact:** [email protected]
### Dataset Summary
team-fight-tactics
### 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 id
- `image`: `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 over `dataset["image"][0]`
- `width`: the image width
- `height`: the image height
- `objects`: a dictionary containing bounding box metadata for the objects present on the image
- `id`: the annotation id
- `area`: the area of the bounding box
- `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#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/team-fight-tactics
### Citation Information
```
@misc{ team-fight-tactics,
title = { team fight tactics Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/object-detection/team-fight-tactics } },
url = { https://universe.roboflow.com/object-detection/team-fight-tactics },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2023-03-29 },
}"
```
### Contributions
Thanks to [@mariosasko](https://github.com/mariosasko) for adding this dataset. |