
<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.




task_categories:object-detection roboflow roboflow2huggingface Self Driving Anpr region:us
{"task_categories": ["object-detection"], "tags": ["roboflow", "roboflow2huggingface", "Self Driving", "Anpr"]}
TAGS
#task_categories-object-detection #roboflow #roboflow2huggingface #Self Driving #Anpr #region-us 


<div align="center">
  <img width="640" alt="keremberke/license-plate-object-detection" src="URL
</div>

### Dataset Labels




### Number of Images




### How to Use

- Install datasets:



- Load the dataset:



### Roboflow Dataset Page
URL

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via URL 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.




### Dataset Labels ### Number of Images ### How to Use

- Install datasets:



- Load the dataset: ### Roboflow Dataset Page
URL ### License
CC BY 4.0 ### Dataset Summary
This dataset was exported via URL 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.
TAGS
#task_categories-object-detection #roboflow #roboflow2huggingface #Self Driving #Anpr #region-us 
 ### Dataset Labels ### Number of Images ### How to Use

- Install datasets:



- Load the dataset: ### Roboflow Dataset Page
URL ### License
CC BY 4.0 ### Dataset Summary
This dataset was exported via URL 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.
passage: TAGS
#task_categories-object-detection #roboflow #roboflow2huggingface #Self Driving #Anpr #region-us 
### Dataset Labels### Number of Images### How to Use

- Install datasets:



- Load the dataset:### Roboflow Dataset Page
URL### License
CC BY 4.0### Dataset Summary
This dataset was exported via URL 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.