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

Example

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.