| --- |
| license: mit |
| tags: |
| - image-classification |
| - indoor-outdoor |
| - real-estate |
| - mobilenetv2 |
| - property-classifier |
| - property-classification |
| - binary-classifier |
| datasets: |
| - airbnb-property-images |
| pipeline_tag: image-classification |
| widget: |
| - src: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/indoor-example.jpg |
| example_title: Indoor Example |
| - src: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/outdoor-example.jpg |
| example_title: Outdoor Example |
| --- |
| |
| # Indoor vs Outdoor Classifier |
|
|
| A binary image classifier that determines whether a property image is indoor or outdoor with 96% accuracy. |
|
|
| ## Model Details |
|
|
| - **Model Type**: MobileNetV2-based binary classifier |
| - **Classes**: Indoor, Outdoor |
| - **Accuracy**: 96% on validation set |
| - **Input Size**: 160x160 RGB images |
|
|
| ## Training Data |
|
|
| The model was trained on 2,000 curated Airbnb property images, split evenly between indoor and outdoor scenes. The dataset was manually verified to ensure high-quality training examples. |
|
|
| ## Use Cases |
|
|
| - Real estate listing automation |
| - Property image organization |
| - Virtual tour preparation |
| - Interior design vs. architecture applications |
|
|
| ## License |
|
|
| This model is released under MIT License. |
