Datasets:
Tasks:
Object Detection
Size:
< 1K
File size: 2,012 Bytes
4892cfb 79ff585 4892cfb 79ff585 4892cfb 79ff585 4892cfb 79ff585 4892cfb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface
- Gaming
---
<div align="center">
<img width="640" alt="keremberke/clash-of-clans-object-detection" src="https://huggingface.co/datasets/keremberke/clash-of-clans-object-detection/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['ad', 'airsweeper', 'bombtower', 'canon', 'clancastle', 'eagle', 'inferno', 'kingpad', 'mortar', 'queenpad', 'rcpad', 'scattershot', 'th13', 'wardenpad', 'wizztower', 'xbow']
```
### Number of Images
```json
{'train': 88, 'test': 13, 'valid': 24}
```
### 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("keremberke/clash-of-clans-object-detection", name="full")
example = ds['train'][0]
```
### Roboflow Dataset Page
[https://universe.roboflow.com/find-this-base/clash-of-clans-vop4y/dataset/5?ref=roboflow2huggingface](https://universe.roboflow.com/find-this-base/clash-of-clans-vop4y/dataset/5?ref=roboflow2huggingface?ref=roboflow2huggingface)
### Citation
```
@misc{ clash-of-clans-vop4y_dataset,
title = { Clash of Clans Dataset },
type = { Open Source Dataset },
author = { Find This Base },
howpublished = { \\url{ https://universe.roboflow.com/find-this-base/clash-of-clans-vop4y } },
url = { https://universe.roboflow.com/find-this-base/clash-of-clans-vop4y },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { feb },
note = { visited on 2023-01-18 },
}
```
### License
CC BY 4.0
### Dataset Summary
This dataset was exported via roboflow.ai on March 30, 2022 at 4:31 PM GMT
It includes 125 images.
CoC 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 1920x1920 (Fit (black edges))
No image augmentation techniques were applied.
|