license-plate-object-detection

<div align="center">
<img width="640" alt="keremberke/license-plate-object-detection" src="https://huggingface.co/datasets/keremberke/license-plate-object-detection/resolve/main/thumbnail.jpg">
</div>

### Dataset Labels

```
['license_plate']
```

### Number of Images

```json
{'train': 6176, 'valid': 1765, 'test': 882}
```

### 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/license-plate-object-detection", name="full")
example = ds['train'][0]
```

### Roboflow Dataset Page
[https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1](https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1?ref=roboflow2huggingface)

### Citation

```
@misc{ vehicle-registration-plates-trudk_dataset,
title = { Vehicle Registration Plates Dataset },
type = { Open Source Dataset },
author = { Augmented Startups },
howpublished = { \\url{ https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk } },
url = { https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jun },
note = { visited on 2023-01-18 },
}
```

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via roboflow.ai on January 13, 2022 at 5:20 PM GMT

It includes 8823 images.
VRP are annotated in COCO format.

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

No image augmentation techniques were applied.

<div align="center">
<img width="640" alt="keremberke/license-plate-object-detection" src="https://huggingface.co/datasets/keremberke/license-plate-object-detection/resolve/main/thumbnail.jpg">
</div>

### 数据集标签

['车牌（license_plate）']

### 图像数量
json
{'训练集': 6176, '验证集': 1765, '测试集': 882}

### 使用方法
- 安装[datasets（数据集库）](https://pypi.org/project/datasets/):
bash
pip install datasets

- 加载数据集：
python
from datasets import load_dataset

ds = load_dataset("keremberke/license-plate-object-detection", name="full")
example = ds['train'][0]

### Roboflow 数据集页面
[https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1](https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1?ref=roboflow2huggingface)

### 引用格式

@misc{ vehicle-registration-plates-trudk_dataset,
title = { 车牌数据集 },
type = { 开源数据集 },
author = { Augmented Startups },
howpublished = { \url{ https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk } },
url = { https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk },
journal = { Roboflow 宇宙 },
publisher = { Roboflow },
year = { 2022 },
month = { 6月 },
note = { 于2023年1月18日访问 },
}

### 许可证
CC BY 4.0

### 数据集概述
本数据集于2022年1月13日格林尼治标准时间17:20通过roboflow.ai导出。
该数据集共包含8823张图像，车牌（Vehicle Registration Plates，简称VRP）采用COCO格式进行标注。
已对每张图像执行以下预处理操作：
* 自动调整像素数据方向（剥离EXIF方向信息）
未应用任何图像增强技术。