SynLiDAR Dataset

Overview

SynLiDAR is a synthetic LiDAR dataset designed for autonomous driving research.
It contains high-quality simulated point cloud sequences and corresponding semantic annotations.

The dataset provides two variants:

• FullDataset — complete version for large-scale experiments (branch: full)
• SubDataset — smaller version suitable for prototyping, debugging, and benchmarking (branch: sub)

This HuggingFace repository uses branches to separate large data files and metadata:

• main → metadata, scripts, annotations
• full → FullDataset
• sub → SubDataset

---

Dataset Structure

SynLiDAR/
├── FullDataset/
│   ├── sequences/
│   │   ├── 00.zip
│   │   ├── …
│   │   └── 12.zip
│   └── readme.txt
│
├── SubDataset/
│   ├── sequences/
│   │   ├── 00.zip
│   │   ├── …
│   │   └── 12.zip
│   └── readme.txt
│
├── annotations.yaml
├── read_data.py
└── README.md

⚠️ Some large sequences have been split into chunks (e.g. 06_part01.zip, 06_part02.zip, …) to avoid exceeding file size limits. These parts are functionally equivalent to the original 06.zip.

---

Contents

• sequences/*.zip — Each zip contains LiDAR frames from a single drive sequence
• annotations.yaml — Semantic categories and label mappings
• read_data.py — Example Python loader to read .bin point cloud files
• readme.txt — Original dataset notes

---

🔽 How to Download the Dataset

Install huggingface_hub

pip install huggingface_hub

Download Full Dataset (branch: full)

from huggingface_hub import snapshot_download

path = snapshot_download(
    repo_id="AR-X/SynLiDAR",
    repo_type="dataset",
    revision="full",
    local_dir="./SynLiDAR",  # specify your desired path
)
print(path)

Download Sub Dataset (branch: sub)

from huggingface_hub import snapshot_download

path = snapshot_download(
    repo_id="AR-X/SynLiDAR",
    repo_type="dataset",
    revision="sub",
    local_dir="./SynLiDAR",  # specify your desired path
)
print(path)

🔧 Merging Split ZIP Files

Some sequences in the full branch were too large (>50GB) and are stored as multiple parts:

Example:

06_part01.zip
06_part02.zip
...
06_part11.zip

These parts correspond to a single original archive. You can merge them into a single folder using Python:

from pathlib import Path

sequence_dir = Path("SynLiDAR/FullDataset/sequences")
# find bases that have part files
bases = sorted({p.stem.split("_part")[0] for p in sequence_dir.glob("*_part*.zip")})

for base in bases:
    parts = sorted(sequence_dir.glob(f"{base}_part*.zip"))
    output_zip = sequence_dir / f"{base}.zip"

    print(f"[{base}] merging {len(parts)} parts -> {output_zip}")
    with open(output_zip, "wb") as out:
        for p in parts:
            with open(p, "rb") as f:
                out.write(f.read())

print("All sequences merged.")

Citation

@inproceedings{xiao2022transfer,  
  title={Transfer learning from synthetic to real lidar point cloud for semantic segmentation},  
  author={Xiao, Aoran and Huang, Jiaxing and Guan, Dayan and Zhan, Fangneng and Lu, Shijian},  
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},  
  volume={36},  
  number={3},  
  pages={2795--2803},  
  year={2022}  
}

⚠️ Disclaimer: This dataset is intended for research and educational usage. Make sure to respect local regulations when training or deploying autonomous driving systems.