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---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-segmentation
tags:
- code
dataset_info:
- config_name: video_01
features:
- name: id
dtype: int32
- name: name
dtype: string
- name: image
dtype: image
- name: mask
dtype: image
- name: shapes
sequence:
- name: track_id
dtype: uint32
- name: label
dtype:
class_label:
names:
'0': referee
'1': background
'2': wrestling
'3': human
- name: type
dtype: string
- name: points
sequence:
sequence: float32
- name: rotation
dtype: float32
- name: occluded
dtype: uint8
- name: z_order
dtype: uint16
- name: attributes
sequence:
- name: name
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 3674
num_examples: 10
download_size: 16130882
dataset_size: 3674
- config_name: video_02
features:
- name: id
dtype: int32
- name: name
dtype: string
- name: image
dtype: image
- name: mask
dtype: image
- name: shapes
sequence:
- name: track_id
dtype: uint32
- name: label
dtype:
class_label:
names:
'0': referee
'1': background
'2': wrestling
'3': human
- name: type
dtype: string
- name: points
sequence:
sequence: float32
- name: rotation
dtype: float32
- name: occluded
dtype: uint8
- name: z_order
dtype: uint16
- name: attributes
sequence:
- name: name
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 3674
num_examples: 10
download_size: 14339322
dataset_size: 3674
- config_name: video_03
features:
- name: id
dtype: int32
- name: name
dtype: string
- name: image
dtype: image
- name: mask
dtype: image
- name: shapes
sequence:
- name: track_id
dtype: uint32
- name: label
dtype:
class_label:
names:
'0': referee
'1': background
'2': wrestling
'3': human
- name: type
dtype: string
- name: points
sequence:
sequence: float32
- name: rotation
dtype: float32
- name: occluded
dtype: uint8
- name: z_order
dtype: uint16
- name: attributes
sequence:
- name: name
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 3674
num_examples: 10
download_size: 15264704
dataset_size: 3674
---
# Fights Segmentation Dataset
The dataset consists of a collection of photos extracted from **videos of fights**. It includes **segmentation masks** for **fighters, referees, mats, and the background**.
The dataset offers a resource for *object detection, instance segmentation, action recognition, or pose estimation*.
It could be useful for **sport community** in identification and detection of the violations, dispute resolution and general optimisation of referee's work using computer vision.
# Get the dataset
### This is just an example of the data
Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=fights-segmentation) to discuss your requirements, learn about the price and buy the dataset.
# Dataset structure
- **images** - contains of original images extracted from the videos of fights
- **masks** - includes segmentation masks created for the original images
- **annotations.xml** - contains coordinates of the polygons and labels, created for the original photo
# Data Format
Each image from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the polygons and labels. For each point, the x and y coordinates are provided.
### Сlasses:
- **human**: fighter or fighters,
- **referee**: referee,
- **wrestling**: mat's area,
- **background**: area above the mat
# Example of XML file structure
# Fights Segmentation might be made in accordance with your requirements.
## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=fights-segmentation) provides high-quality data annotation tailored to your needs
More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**
TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** |