IndoorOutdoorNet-20K

# **IndoorOutdoorNet-20K**

**IndoorOutdoorNet-20K** is a labeled image dataset designed for the task of **image classification**, particularly focused on distinguishing between **indoor** and **outdoor** scenes. The dataset is publicly available on [Hugging Face Datasets](https://huggingface.co/datasets/prithivMLmods/IndoorOutdoorNet-20K) and is useful for scene understanding, transfer learning, and model benchmarking.

## Dataset Summary

- **Task**: Image Classification
- **Modalities**: Image
- **Labels**: Indoor, Outdoor (2 classes)
- **Total Images**: 19,998
- **Split**: Train (100%)
- **Languages**: English (metadata)
- **Size**: ~451 MB
- **License**: Apache-2.0

## Features

| Column | Type | Description |
|--------|--------|---------------------------------|
| image | Image | Input image file |
| label | Class | Scene label: `Indoor` or `Outdoor` |

## Example

| Image | Label |
|------------------------------|---------|
|  | Indoor |
|  | Outdoor |

> Note: For full visualization, visit the dataset viewer on Hugging Face.

## Usage

You can use this dataset directly with the `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/IndoorOutdoorNet-20K")
```

To visualize a sample:

```python
import matplotlib.pyplot as plt

sample = dataset['train'][0]
plt.imshow(sample['image'])
plt.title(sample['label'])
plt.axis('off')
plt.show()
```

## Applications

- Scene classification
- Image context recognition
- Smart surveillance
- Autonomous navigation
- Indoor-outdoor transition detection in robotics

## Citation

If you use this dataset in your research or project, please cite it appropriately. (You can include a BibTeX entry here if available.)

## License

This dataset is licensed under the Apache 2.0 License.

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

# **IndoorOutdoorNet-20K**

**IndoorOutdoorNet-20K** 是一款专为**图像分类**任务打造的标注图像数据集，核心聚焦于**室内（Indoor）**与**室外（Outdoor）**场景的区分。该数据集已在[Hugging Face Datasets](https://huggingface.co/datasets/prithivMLmods/IndoorOutdoorNet-20K) 公开，可用于场景理解、迁移学习以及模型基准测试。

## 数据集概览

- **任务类型**：图像分类
- **模态**：图像
- **标签类别**：室内、室外（共2类）
- **总图像数**：19998张
- **数据集拆分**：训练集（占比100%）
- **元数据语言**：英文
- **数据集体积**：约451 MB
- **开源协议**：Apache-2.0

## 数据集字段说明

| 字段名 | 数据类型 | 描述说明 |
|--------|----------|------------------------------|
| image | 图像 | 输入图像文件 |
| label | 类别标签 | 场景标签：`Indoor`（室内）或`Outdoor`（室外） |

## 示例样本

| 图像示例 | 标签类别 |
|------------------------------|----------|
|  | 室内 |
|  | 室外 |

> 注：如需查看完整可视化样本，请访问Hugging Face平台的数据集查看页面。

## 使用方法

您可以直接通过`datasets`库加载该数据集：

python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/IndoorOutdoorNet-20K")

如需可视化样本：

python
import matplotlib.pyplot as plt

sample = dataset['train'][0]
plt.imshow(sample['image'])
plt.title(sample['label'])
plt.axis('off')
plt.show()

## 应用场景

- 场景分类任务
- 图像上下文识别
- 智能安防监控
- 自主导航系统
- 机器人领域的室内外场景过渡检测

## 引用说明

若您的研究或项目中使用了本数据集，请进行规范引用。（若有可用的BibTeX引用条目，可在此处补充。）

## 开源协议

本数据集采用Apache 2.0开源协议进行授权。

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*本数据集由[@prithivMLmods](https://huggingface.co/prithivMLmods) 整理并维护。*