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| license: mit |
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|
| ## This is a indoor building element dataset with 37 classes. |
| This dataset consists of **900 original images** collected from the ETH building videos collected by Aria glasses, Excel sheet: `230116_Ernest-Bloch_Inventaire` and web-scraped samples from [gruner-reuse.ch](https://www.gruner-reuse.ch/produkte) using the script **`parse_grunerweb.ipynb`**. The dataset is randomly split into **720 training**, **90 validation**, and **90 test** images. |
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| After applying data augmentations, the final dataset contains a total of **2,340 images**, including: |
| - **2,160 augmented training samples** |
| - **90 validation samples** |
| - **90 test samples** |
| |
| ### Preprocessing |
| - **Auto-Orient**: Applied |
| - **Resize**: Stretched to 640×640 |
| - **Auto-Adjust Contrast**: Using Adaptive Equalization |
| |
| ### Augmentations |
| Each training example is augmented to generate **3 output variations** with the following transformations: |
| |
| - **Hue**: Between −15° and +15° |
| - **Saturation**: Between −25% and +25% |
| - **Brightness**: Between −15% and +15% |
| - **Blur**: Up to 1px |
| - **Noise**: Up to 0.1% of pixels |
| |
| ### Coco format: |
| <pre> ``` |
| data_new_coco/ |
| ├── train/ |
| │ ├── images/ |
| │ └── annotations/ |
| ├── valid/ |
| │ ├── images/ |
| │ └── annotations/ |
| ├── test/ |
| │ ├── images/ |
| │ └── annotations/ |
| ├── README.dataset.txt |
| └── README.roboflow.txt |
| ``` </pre> |
| |
| ### Yolo format: |
| <pre> ``` |
| data_new_yolo/ |
| ├── train/ |
| │ ├── images/ |
| │ └── labels/ |
| ├── valid/ |
| │ ├── images/ |
| │ └── labels/ |
| ├── test/ |
| │ ├── images/ |
| │ └── labels/ |
| ├── data.yaml |
| ├── README.dataset.txt |
| └── README.roboflow.txt |
| ``` </pre> |
