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--- |
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license: mit |
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pretty_name: Taiwan License Plate Dataset |
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annotations_creators: |
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- expert-generated |
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language: |
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- en |
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- zh |
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multilinguality: monolingual |
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size_categories: |
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- 1K<n<10K |
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source_datasets: |
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- original |
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task_categories: |
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- object-detection |
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tags: |
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- license-plate |
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- polygon |
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- labelme |
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--- |
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# TLPD: Taiwan License Plate Dataset |
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TLPD is a dataset containing over 3,000 images of vehicles with annotated license plates. Each image is labeled using the [LabelMe](https://github.com/wkentaro/labelme) format, with polygon annotations describing the boundary of each license plate. |
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This dataset is designed for tasks such as license plate detection, polygon segmentation, and scene text detection. |
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## 📁 Dataset Structure |
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All image files are stored in the `images/` directory, and their corresponding polygon annotations are in the `labels/` directory: |
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``` |
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images/ |
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├── 0001.jpg |
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├── 0002.jpg |
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└── ... |
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labels/ |
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├── 0001.json |
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├── 0002.json |
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└── ... |
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``` |
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Each `.jpg` image is paired with a `.json` file of the same name containing the polygon annotation (in LabelMe format). |
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## 🏷️ Annotation Format (LabelMe) |
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Each `.json` file includes: |
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- `"imagePath"`: the name of the image |
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- `"shapes"[0]["label"]`: `"carplate"` |
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- `"shapes"[0]["points"]`: polygon points in the format `[[x1, y1], [x2, y2], ...]` |
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- `"imageHeight"`, `"imageWidth"`: image dimensions |
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### Example JSON snippet: |
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```json |
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{ |
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"imagePath": "0001.jpg", |
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"shapes": [ |
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{ |
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"label": "carplate", |
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"points": [ |
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[5.0, 8.0], |
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[117.0, 12.0], |
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[115.0, 52.0], |
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[3.0, 48.0] |
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], |
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"shape_type": "polygon" |
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} |
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], |
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"imageHeight": 60, |
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"imageWidth": 121 |
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} |
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``` |
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## 💻 How to Use |
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To load this dataset using the Hugging Face 🤗 `datasets` library: |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("evan6007/TLPD", data_dir=".", trust_remote_code=True) |
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sample = ds["train"][0] |
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image = sample["image"] # PIL image |
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label = sample["label"] # "carplate" |
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points = sample["points"] # [[x1, y1], ..., [x4, y4]] |
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``` |
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> Note: This dataset requires a custom loading script (`dataset.py`). Be sure to set `trust_remote_code=True`. |
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## 🧑🔬 Intended Use |
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- Object Detection (license plate) |
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- Polygon segmentation |
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- Scene text analysis |
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- Few-shot detection tasks |
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## 🪪 License |
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This dataset is licensed under the **MIT License**. You are free to use, share, and modify it for both academic and commercial purposes, with attribution. |
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## ✍️ Citation |
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``` |
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@misc{TLPD2025, |
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title={Taiwan License Plate Dataset}, |
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author={Hoi Lee ,Jui-Hung Weng, Chao-Hsiang Hsiao}, |
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year={2025}, |
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howpublished={\url{https://huggingface.co/datasets/evan6007/TLPD}} |
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} |
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``` |
