Multilabel-GeoSceneNet-16K

# **Multilabel-GeoSceneNet-16K**

**Multilabel-GeoSceneNet-16K** is a geospatial image dataset for **multi-label scene classification**. Each image may belong to one or more geographic scene categories, making it suitable for multi-label learning tasks in remote sensing and geospatial analytics.

## Dataset Summary

- **Task**: Multi-label Image Classification
- **Modalities**: Image
- **Total Images**: 16,033
- **Split**: Train (100%)
- **Labels**: 7 categories (multi-label)
- **License**: Apache-2.0
- **Size**: ~227 MB

## Labels

Each image may be annotated with one or more of the following scene categories:

| Label ID | Class Name |
|----------|--------------------------|
| 0 | Buildings and Structures |
| 1 | Desert |
| 2 | Forest Area |
| 3 | Hill or Mountain |
| 4 | Ice Glacier |
| 5 | Sea or Ocean |
| 6 | Street View |

```py
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("prithivMLmods/Multilabel-GeoSceneNet-16K")

# Extract unique labels
labels = dataset["train"].features["label"].names

# Create id2label mapping
id2label = {str(i): label for i, label in enumerate(labels)}

# Print the mapping
print(id2label)
```

```
{'0': 'Buildings and Structures', '1': 'Desert', '2': 'Forest Area', '3': 'Hill or Mountain', '4': 'Ice Glacier', '5': 'Sea or Ocean', '6': 'Street View'}
```

## Features

| Column | Type | Description |
|--------|--------|---------------------------------------------|
| image | Image | Image input in JPEG format |
| label | List | List of class labels for the given image |

## Example

| Image | Label(s) |
|------------------------------|---------------------------|
|  | Buildings and Structures |
|  | Forest Area, Hill or Mountain |

> Note: For best experience, browse the dataset directly on [Hugging Face](https://huggingface.co/datasets/prithivMLmods/Multilabel-GeoSceneNet-16K).

## Usage

You can load the dataset using the `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Multilabel-GeoSceneNet-16K")
```

To visualize an example:

```python
import matplotlib.pyplot as plt

example = dataset['train'][0]
plt.imshow(example['image'])
plt.title(", ".join(example['label']))
plt.axis('off')
plt.show()
```

## Applications

- Geospatial scene understanding
- Remote sensing analytics
- Environmental monitoring
- Land cover classification
- AI-assisted mapping

## License

This dataset is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).

---

*Curated & Maintained by [@prithivMLmods](https://huggingface.co/prithivMLmods).*

# **Multilabel-GeoSceneNet-16K**

**Multilabel-GeoSceneNet-16K** 是一款用于**多标签场景分类（multi-label scene classification）**的地理空间图像数据集。每张图像可隶属于一个或多个地理场景类别，适用于遥感与地理空间分析领域的多标签学习任务。

## 数据集概览
- **任务类型**：多标签图像分类
- **模态**：图像
- **总图像数**：16033张
- **数据集划分**：仅训练集（占比100%）
- **标签类别**：7个多标签分类类别
- **开源协议**：Apache-2.0
- **数据集大小**：约227 MB

## 标签体系
每张图像可被标注为以下一个或多个场景类别：

| 标签ID | 类别名称 |
|--------|--------------------------|
| 0 | 建筑物与构筑物（Buildings and Structures） |
| 1 | 沙漠（Desert） |
| 2 | 林区（Forest Area） |
| 3 | 丘陵或山地（Hill or Mountain） |
| 4 | 冰川（Ice Glacier） |
| 5 | 海洋（Sea or Ocean） |
| 6 | 街景（Street View） |

py
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("prithivMLmods/Multilabel-GeoSceneNet-16K")

# Extract unique labels
labels = dataset["train"].features["label"].names

# Create id2label mapping
id2label = {str(i): label for i, label in enumerate(labels)}

# Print the mapping
print(id2label)

{'0': 'Buildings and Structures', '1': 'Desert', '2': 'Forest Area', '3': 'Hill or Mountain', '4': 'Ice Glacier', '5': 'Sea or Ocean', '6': 'Street View'}

## 数据字段说明
| 列名 | 数据类型 | 描述说明 |
|--------|----------|------------------------------------------|
| image | 图像 | JPEG格式的图像输入数据 |
| label | 列表 | 当前图像对应的类别标签列表 |

## 示例
| 图像示例 | 标签类别 |
|------------------------------|---------------------------|
|  | 建筑物与构筑物（Buildings and Structures） |
|  | 林区（Forest Area）、丘陵或山地（Hill or Mountain） |

> 注意：如需获得最佳浏览体验，请直接在[Hugging Face](https://huggingface.co/datasets/prithivMLmods/Multilabel-GeoSceneNet-16K)平台浏览该数据集。

## 使用方法
你可通过`datasets`库加载该数据集：
python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Multilabel-GeoSceneNet-16K")

如需可视化示例数据：
python
import matplotlib.pyplot as plt

example = dataset['train'][0]
plt.imshow(example['image'])
plt.title(", ".join(example['label']))
plt.axis('off')
plt.show()

## 应用场景
- 地理空间场景理解
- 遥感数据分析
- 环境监测
- 土地覆盖分类
- AI辅助制图

## 开源协议
本数据集采用[Apache 2.0开源协议](https://www.apache.org/licenses/LICENSE-2.0)进行授权。

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*由[@prithivMLmods](https://huggingface.co/prithivMLmods) 整理并维护。*