task_categories:object-detection region:us roboflow roboflow2huggingface
---
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface

---

<div align="center">
  <img width="640" alt="neogpx/constructioncazo" src="https://huggingface.co/datasets/neogpx/constructioncazo/resolve/main/thumbnail.jpg">
</div>

### Dataset Labels

```
['building']
```


### Number of Images

```json
{'valid': 106, 'test': 738, 'train': 1171}
```


### How to Use

- Install [datasets](https://pypi.org/project/datasets/):

```bash
pip install datasets
```

- Load the dataset:

```python
from datasets import load_dataset

ds = load_dataset("neogpx/constructioncazo", name="full")
example = ds['train'][0]
```

### Roboflow Dataset Page
[https://universe.roboflow.com/trees-detection/building-detection-scazo/dataset/1
](https://universe.roboflow.com/trees-detection/building-detection-scazo/dataset/1
?ref=roboflow2huggingface)

### Citation

```
@misc{
                            building-detection-scazo_dataset,
                            title = { Building detection Dataset },
                            type = { Open Source Dataset },
                            author = { Trees detection },
                            howpublished = { \\url{ https://universe.roboflow.com/trees-detection/building-detection-scazo } },
                            url = { https://universe.roboflow.com/trees-detection/building-detection-scazo },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { nov },
                            note = { visited on 2025-02-14 },
                            }
```

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via roboflow.com on November 29, 2023 at 11:18 AM GMT

Roboflow is an end-to-end computer vision platform that helps you
* collaborate with your team on computer vision projects
* collect & organize images
* understand and search unstructured image data
* annotate, and create datasets
* export, train, and deploy computer vision models
* use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset,
visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 2015 images.
Buildings are annotated in COCO format.

The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 640x640 (Stretch)

No image augmentation techniques were applied.



