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  ---
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  license: mit
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  pretty_name: SynLiDAR
 
 
 
 
 
 
 
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  ---
 
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  # SynLiDAR Dataset
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  ## Overview
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- SynLiDAR is a synthetic LiDAR dataset designed for autonomous driving research.
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  It contains high-quality simulated point cloud sequences and corresponding semantic annotations.
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  The dataset provides two variants:
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- - FullDataset – complete version for large-scale experiments
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- - SubDataset smaller version suitable for prototyping, debugging, and benchmarking
 
 
 
 
 
 
 
 
 
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  ## Dataset Structure
 
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  ```
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- SynLiDAR/
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- ├── FullDataset/
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- │ ├── sequences/
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- │ │ ├── 00.zip
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- │ │ ├── ...
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- │ │ └── 12.zip
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- │ └── readme.txt
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-
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- ├── SubDataset/
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- │ ├── sequences/
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- │ │ ├── 00.zip
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- │ │ ├── ...
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- │ │ └── 12.zip
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- │ └── readme.txt
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-
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- ├── annotations.yaml
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- ├── read_data.py
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- └── README.md
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  ```
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  ## Contents
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- - sequences/*.zip — Each zip contains LiDAR frames
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- - annotations.yaml — Semantic categories and their mappings
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- - read_data.py — Example Python loader
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- - readme.txt — Additional notes from the original dataset
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- ## License
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- The SynLiDAR dataset in this repository is released under the MIT License.
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- MIT License
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-
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- Copyright (c) 2025 Aoran XIAO
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-
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- Permission is hereby granted, free of charge, to any person obtaining a copy
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- of this software and associated documentation files (the "Software"), to deal
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- in the Software without restriction, including without limitation the rights
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- to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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- copies of the Software, and to permit persons to whom the Software is
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- furnished to do so, subject to the following conditions:
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-
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- The above copyright notice and this permission notice shall be included in all
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- copies or substantial portions of the Software.
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-
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- THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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- IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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- FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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- AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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- LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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- OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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- SOFTWARE.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- ⚠️ **Disclaimer**: This dataset is intended for research and educational usage.
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- Make sure to respect local regulations when training or deploying autonomous driving systems.
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  ## Citation
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  ```
@@ -81,4 +139,8 @@ Make sure to respect local regulations when training or deploying autonomous dri
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  pages={2795--2803},
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  year={2022}
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  }
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- ```
 
 
 
 
 
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  ---
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  license: mit
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  pretty_name: SynLiDAR
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+ tags:
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+ - lidar
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+ - synthetic
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+ - point-cloud
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+ - autonomous-driving
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+ - semantic-segmentation
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+ - 3D-segmentation
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  ---
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+
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  # SynLiDAR Dataset
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  ## Overview
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+ **SynLiDAR** is a synthetic LiDAR dataset designed for autonomous driving research.
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  It contains high-quality simulated point cloud sequences and corresponding semantic annotations.
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  The dataset provides two variants:
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+
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+ - **FullDataset** complete version for large-scale experiments (branch: `full`)
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+ - **SubDataset** — smaller version suitable for prototyping, debugging, and benchmarking (branch: `sub`)
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+
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+ This HuggingFace repository uses **branches** to separate large data files and metadata:
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+
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+ - `main` → metadata, scripts, annotations
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+ - `full` → FullDataset
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+ - `sub` → SubDataset
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+
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+ ---
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  ## Dataset Structure
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+
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  ```
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+ SynLiDAR/
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+ ├── FullDataset/
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+ │ ├── sequences/
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+ │ │ ├── 00.zip
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+ │ │ ├──
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+ │ │ └── 12.zip
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+ │ └── readme.txt
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+
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+ ├── SubDataset/
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+ │ ├── sequences/
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+ │ │ ├── 00.zip
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+ │ │ ├──
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+ │ │ └── 12.zip
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+ │ └── readme.txt
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+
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+ ├── annotations.yaml
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+ ├── read_data.py
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+ └── README.md
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  ```
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+ > ⚠️ Some large sequences have been split into chunks (e.g. `06_part01.zip`, `06_part02.zip`, …) to avoid exceeding file size limits.
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+ > These parts are functionally equivalent to the original `06.zip`.
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+
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+ ---
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+
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  ## Contents
 
 
 
 
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+ - `sequences/*.zip` — Each zip contains LiDAR frames from a single drive sequence
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+ - `annotations.yaml` Semantic categories and label mappings
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+ - `read_data.py` — Example Python loader to read `.bin` point cloud files
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+ - `readme.txt` — Original dataset notes
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+
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+ ---
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+
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+ # 🔽 How to Download the Dataset
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+
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+ ## Install huggingface_hub
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+
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+ ```bash
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+ pip install huggingface_hub
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  ```
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+ ## Download Full Dataset (branch: full)
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+
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+ ```python
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+ from huggingface_hub import snapshot_download
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+
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+ path = snapshot_download(
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+ repo_id="AR-X/SynLiDAR",
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+ revision="full",
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+ )
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+ print(path)
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+ ```
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+
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+ ## Download Sub Dataset (branch: sub)
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+
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+ ```python
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+ from huggingface_hub import snapshot_download
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+
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+ path = snapshot_download(
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+ repo_id="AR-X/SynLiDAR",
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+ revision="sub",
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+ )
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+ print(path)
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+ ```
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+ ## 🔧 Merging Split ZIP Files
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+
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+ Some sequences in the full branch were too large (>50GB) and are stored as multiple parts:
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+
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+ Example:
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+ ```
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+ 06_part01.zip
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+ 06_part02.zip
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+ ...
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+ 06_part11.zip
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+ ```
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+
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+ These parts correspond to a single original archive. You can merge them into a single folder using Python:
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+
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+ ```python
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+ import zipfile
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+ from pathlib import Path
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+
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+ sequence_dir = Path("SynLiDAR/FullDataset/sequences")
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+ parts = sorted(sequence_dir.glob("06_part*.zip"))
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+
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+ output = Path("merged_06")
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+ output.mkdir(exist_ok=True)
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+
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+ for z in parts:
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+ print("Extracting", z.name)
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+ with zipfile.ZipFile(z, "r") as zp:
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+ zp.extractall(output)
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  ```
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  ## Citation
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  ```
 
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  pages={2795--2803},
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  year={2022}
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  }
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+ ```
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+
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+
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+ ⚠️ **Disclaimer**: This dataset is intended for research and educational usage.
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+ Make sure to respect local regulations when training or deploying autonomous driving systems.