---
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: width
    dtype: uint16
  - name: height
    dtype: uint16
  - name: shapes
    sequence:
    - 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: int16
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 45562
    num_examples: 10
  download_size: 16130822
  dataset_size: 45562
- config_name: video_02
  features:
  - name: id
    dtype: int32
  - name: name
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: width
    dtype: uint16
  - name: height
    dtype: uint16
  - name: shapes
    sequence:
    - 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: int16
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 61428
    num_examples: 10
  download_size: 14339242
  dataset_size: 61428
- config_name: video_03
  features:
  - name: id
    dtype: int32
  - name: name
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: width
    dtype: uint16
  - name: height
    dtype: uint16
  - name: shapes
    sequence:
    - 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: int16
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 42854
    num_examples: 9
  download_size: 13763862
  dataset_size: 42854
---
# UFC/MMA Fights Images Segmentation, Sport 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**. 

# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=fights-segmentation)** to buy the dataset

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.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F528c5d5de741e46d8754a5a67ff476fc%2FFrame%2024.png?generation=1695968589650484&alt=media)

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets?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

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F538310907b1e8b4c6f07f456331fe091%2Fcarbon.png?generation=1695969032771522&alt=media)

# Fights Segmentation might be made in accordance with your requirements.

## **[TrainingData](https://trainingdata.pro/datasets?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**

*keywords: body segmentation dataset, human segmentation dataset, human body segmentation, people images dataset, biometric data dataset, biometric dataset, ufc athletes, sports dataset, ultimate fighting championship,  semantic segmentation, computer vision, deep learning, machine learning, image dataset, image classification, human images*