justjuu/rtdetr-v2-license-plate-detection
Object Detection
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in Data Studio
License Plate Detection Dataset
Overview
This dataset is designed for License Plate Detection using modern object detection models such as RT-DETR, DETR, YOLO, etc.
It is a cleaned and simplified version of a Roboflow-exported COCO dataset, converted into Hugging Face Datasets format for easy training, evaluation, and reuse.
The dataset contains only one object class: license_plate, making it ideal for single-class detection tasks and real-time pipelines.
Dataset Structure
The dataset is organized into three splits:
trainvalidationtest
Each sample contains:
- An image
- One or more bounding boxes for license plates
Bounding boxes follow the COCO format: (x_min, y_min, width, height)
Classes
This is a single-class object detection dataset.
| Class ID | Class Name |
|---|---|
| 0 | license_plate |
📥 Downloading the Dataset
This dataset can be downloaded and used directly with the Hugging Face datasets library.
from datasets import load_dataset
dataset = load_dataset("justjuu/real-time-license-plate-detection-coco-hf")
The dataset will be loaded with the following splits:
traintestvalid
🔧 Example Usage
sample = dataset["train"][0]
image = sample["image"]
bboxes = sample["objects"]["bbox"]
labels = sample["objects"]["category"]
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Size of downloaded dataset files:
237 MB
Size of the auto-converted Parquet files:
237 MB
Number of rows:
8,823
Models trained or fine-tuned on justjuu/license-plate-detection