metadata

license: apache-2.0
task_categories:
  - image-classification
language:
  - en
tags:
  - Indoor
  - Outdoor
  - Scene
  - Classification
  - 20K
  - Net
size_categories:
  - 10K<n<100K

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 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:

from datasets import load_dataset

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

To visualize a sample:

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.

Curated & Maintained by @prithivMLmods.