pyronear/openfire

---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language: []
license:
- apache-2.0
multilinguality: []
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- image-classification
task_ids: []
pretty_name: Wildfire image classification dataset collected using images from web
searches.
---

# Dataset Card for OpenFire

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://pyronear.org/pyro-vision/datasets.html#openfire
- **Repository:** https://github.com/pyronear/pyro-vision
- **Point of Contact:** Pyronear <https://pyronear.org/en/>

### Dataset Summary

OpenFire is an image classification dataset for wildfire detection, collected
from web searches.

### Supported Tasks and Leaderboards

- `image-classification`: The dataset can be used to train a model for Image Classification.

### Languages

English

## Dataset Structure

### Data Instances

A data point comprises an image URL and its binary label.

```
{
'image_url': 'https://cdn-s-www.ledauphine.com/images/13C08274-6BA6-4577-B3A0-1E6C1B2A573C/FB1200/photo-1338240831.jpg',
'is_wildfire': true,
}
```

### Data Fields

- `image_url`: the download URL of the image.
- `is_wildfire`: a boolean value specifying whether there is an ongoing wildfire on the image.

### Data Splits

The data is split into training and validation sets. The training set contains 7143 images and the validation set 792 images.

## Dataset Creation

### Curation Rationale

The curators state that the current wildfire classification datasets typically contain close-up shots of wildfires, with limited variations of weather conditions, luminosity and backrgounds,
making it difficult to assess for real world performance. They argue that the limitations of datasets have partially contributed to the failure of some algorithms in coping
with sun flares, foggy / cloudy weather conditions and small scale.

### Source Data

#### Initial Data Collection and Normalization

OpenFire was collected using images publicly indexed by the search engine DuckDuckGo using multiple relevant queries. The images were then manually cleaned to remove errors.

### Annotations

#### Annotation process

Each web search query was designed to yield a single label (with wildfire or without), and additional human verification was used to remove errors.

#### Who are the annotators?

François-Guillaume Fernandez

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

François-Guillaume Fernandez

### Licensing Information

[Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).

### Citation Information

```
@software{Pyronear_PyroVision_2019,
title={Pyrovision: wildfire early detection},
author={Pyronear contributors},
year={2019},
month={October},
publisher = {GitHub},
howpublished = {\url{https://github.com/pyronear/pyro-vision}}
}
```

原始信息汇总

数据集概述

数据集基本信息

• 名称: OpenFire
• 类型: 图像分类数据集
• 目的: 用于野火检测
• 数据来源: 网络搜索
• 语言: 英语
• 许可证: Apache-2.0
• 数据量: 1K<n<10K
• 多语言性: 不适用
• 任务类别: 图像分类

数据集结构

• 数据实例: 每个数据点包含一个图像URL和一个二元标签（是否存在野火）。
• 数据字段:
  • image_url: 图像下载URL。
  • is_wildfire: 布尔值，指示图像中是否存在野火。
• 数据分割: 数据分为训练集和验证集，训练集包含7143张图像，验证集包含792张图像。

数据集创建

• 采集与规范化: 数据通过DuckDuckGo搜索引擎收集，并经过手动清理。
• 标注过程: 每个网络搜索查询产生一个标签（有或无野火），并进行了人工验证以移除错误。
• 标注者: François-Guillaume Fernandez

使用考虑

• 数据集影响: 待补充
• 偏见讨论: 待补充
• 其他已知限制: 待补充

附加信息

• 数据集管理员: François-Guillaume Fernandez
• 许可证信息: Apache License 2.0
• 引用信息: 见README文件中的引用格式