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license: mit
---
## 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.
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> |