Voxel51/Football-Player-Segmentation

---
annotations_creators: []
language: en
license: cc0-1.0
size_categories:
- n<1K
task_categories:
- object-detection
task_ids: []
pretty_name: football-player-segmentation
tags:
- fiftyone
- image
- object-detection
dataset_summary: '


This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 512 samples.

## Installation

If you haven''t already, install FiftyOne:

```bash

pip install -U fiftyone

```

## Usage

```python

import fiftyone as fo

import fiftyone.utils.huggingface as fouh

# Load the dataset

# Note: other available arguments include ''max_samples'', etc

dataset = fouh.load_from_hub("Voxel51/Football-Player-Segmentation")

# Launch the App

session = fo.launch_app(dataset)

```

'
---

# Dataset Card for football-player-segmentation

This dataset is specifically designed for computer vision tasks related to player detection and segmentation in foot goalkeeperders, and forwards, captured from various angles and distances.


This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 512 samples.

## Installation

If you haven't already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
import fiftyone as fo
import fiftyone.utils.huggingface as fouh

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/Football-Player-Segmentation")

# Launch the App
session = fo.launch_app(dataset)
```

## Dataset Details

### Dataset Description

This dataset is specifically designed for computer vision tasks related to player detection and segmentation in football matches. The dataset contains images of players in different playing positions, such as goalkeepers, defenders, midfielders, and forwards, captured from various angles and distances. The images are annotated with pixel-level masks that indicate the player's location and segmentation boundaries, making it ideal for training deep learning models for player segmentation. The dataset is suitable for researchers and developers working on football-related computer vision applications, such as tracking players during a match or analysing player movements and behaviours. It is also useful for sports analysts and enthusiasts who want to explore player performance metrics and trends based on positional data. Overall, this football player segmentation dataset is a valuable resource for anyone interested in advancing computer vision techniques for sports analysis and tracking.

- **Language(s) (NLP):** en
- **License:** cc0-1.0

### Dataset Sources

<!-- Provide the basic links for the dataset. -->

- **Original Source:** [kaggle](https://www.kaggle.com/datasets/ihelon/football-player-segmentation)

## Uses

- Object Detection
- Segmentation

## Dataset Structure

The dataset contains two fields, `detections` and `segmentations` across 512 different samples

原始信息汇总

数据集概述

基本信息

• 数据集名称： football-player-segmentation
• 语言： en
• 许可证： cc0-1.0
• 样本数量： 512

任务与应用

• 任务类别： object-detection
• 应用领域：
  • 对象检测
  • 分割

数据集内容

• 描述： 该数据集专为足球比赛中球员检测和分割的计算机视觉任务设计。数据集包含不同位置的球员（如守门员、后卫、中场和前锋）在各种角度和距离下的图像。图像通过像素级掩码进行标注，指示球员的位置和分割边界，适合训练深度学习模型进行球员分割。

数据集结构

• 数据字段： 包含detections和segmentations两个字段。
• 样本数量： 512个样本。