marjandl/BigEarthNet-19-HMLC

---
license: mit
task_categories:
- image-classification
---

# Extended label set of BigEarthNet-19 for Hierarchical Multi-Label Classification

This dataset contains an extended version of the original label set of BigEarthNet-19 for Hierarchical Multi-Label Classification.

## Dataset creation

It was created based on the CORINE Land Cover database of the year 2018 (CLC 2018), which provides detailed information about the land cover classes at multiple levels of the hierarchy

## Loading the Dataset

To load the dataset into your project, you can use the following code snippet:

```python
import pandas as pd
from datasets import load_dataset

# Load the dataset from Hugging Face
dataset = load_dataset(
"marjandl/BigEarthNet-19-HMLC",
split='train'
)

data = [line.split('\t')[1:] for line in dataset['text']]
df = pd.DataFrame(data)

# Set the first row as the header and drop it from the DataFrame
df.columns = df.iloc[0]
df = df.drop(0).reset_index(drop=True)

原始信息汇总

Extended label set of BigEarthNet-19 for Hierarchical Multi-Label Classification

数据集概述

• 数据集名称: Extended label set of BigEarthNet-19 for Hierarchical Multi-Label Classification
• 任务类别: 图像分类
• 许可证: MIT

数据集创建

• 创建依据: 基于2018年的CORINE土地覆盖数据库（CLC 2018），该数据库提供了关于土地覆盖类别的详细信息，涵盖多个层次的层次结构。

数据集加载

• 加载方式: 使用Hugging Face的load_dataset函数加载数据集。

• 示例代码: python import pandas as pd from datasets import load_dataset

  从Hugging Face加载数据集

  dataset = load_dataset( "marjandl/BigEarthNet-19-HMLC", split=train )

  data = [line.split( )[1:] for line in dataset[text]] df = pd.DataFrame(data)

  将第一行设置为表头并从DataFrame中删除

  df.columns = df.iloc[0] df = df.drop(0).reset_index(drop=True)