lothanspace/change4-tcm-dataset

Chang'E-4 TCM Dataset

LabelMe terrain annotations for Chang'E-4 Yutu-2 rover imagery.

Dataset: Segmentation masks are available on Hugging Face.

Note: Original Chang'E-4 images are not included due to copyright restrictions. You must download the source images directly from CLPDS (see instructions below).

Quick Start

# Install dependencies
pip install -r requirements.txt

# Build the Hugging Face JSONL manifest from raw annotations
python scripts/prepare_dataset.py --hf-jsonl

# Generate local mask PNGs and metadata from annotations
python scripts/prepare_dataset.py

# Convert PDS files to images (requires raw data from CLPDS)
python scripts/convert_pds.py data/raw data/images

For the Hugging Face dataset, publish only files under data/masks/. Generate data/masks/train.jsonl from the stripped LabelMe annotations so the dataset viewer can stream rows reliably.

Annotation Format

Each dataset row comes from data/masks/train.jsonl, with one stripped LabelMe annotation per line. The shapes field contains polygon or rectangle regions with the labels below.

Class Labels

Index	Label
0	background
1	crater
2	shadow
3	surface
4	rock
5	soil
6	rover
7	space
8	rocker

Downloading Chang'E-4 Data

Data is available from China's Lunar and Planetary Data System (CLPDS).

1. Register an Account

1. Go to https://clpds.bao.ac.cn
2. Create an account (check spam folder for confirmation email from NAOC)

2. Download Data

1. Navigate to Chang'E-4 data search: https://clpds.bao.ac.cn/ce5web/searchOrder-ce4En.do
2. Select an instrument:
   • PCAM - Panoramic Camera (rover, stereo pairs)
   • TCAM - Terrain Camera (lander)
   • LPR - Lunar Penetrating Radar
   • VNIS - Visible/Near-IR Spectrometer
3. Choose data level (L2A or higher for calibrated data)
4. Add files to cart and process order
5. Download and extract to data/raw/

Data Format

Chang'E-4 uses PDS4 format:

• XML label file (.xml) - metadata
• Data file (.img, *L) - image data

Converting to Images

The conversion script applies debayering and contrast stretching:

# Convert all PDS files in data/raw to PNG
python scripts/convert_pds.py data/raw data/images

# Preview files without converting
python scripts/convert_pds.py data/raw data/images --dry-run

# Flatten output to single directory
python scripts/convert_pds.py data/raw data/images --flat

Processing Steps

1. Read PDS4 file using pds4_tools
2. Debayer raw Bayer images (PCAM full-resolution)
3. Apply 2% linear contrast stretch
4. Save as PNG

Project Structure

├── data/
│   ├── masks/           # LabelMe annotation JSONs
│   │   └── train.jsonl  # HF streaming manifest generated from masks/
│   ├── masks_png/       # Indexed mask PNGs (generated locally)
│   ├── metadata.jsonl   # Local metadata for derived assets
│   ├── class_labels.json
│   ├── raw/             # Downloaded PDS4 files (you provide)
│   └── images/          # Converted PNG images (generated)
├── docs/
│   └── chinese-moon-data-access.md
├── scripts/
│   ├── convert_pds.py
│   └── prepare_dataset.py
└── requirements.txt

References

• CLPDS Data Portal
• Chang'E-4 Data Releases
• CLPDS Overview Paper

Citation

If you use this dataset in your research, please cite:

@misc{chang4tcm2026,
  author       = {Yu, Sam and Huang, Christoper and Nasika, Tanvi and Shao, Yi and Singhania, Amay},
  title        = {Chang'E-4 Terrain Classification Dataset},
  year         = {2026},
  organization = {Lothan Space, IHS Maker Club},
  publisher    = {HuggingFace},
  url          = {https://huggingface.co/datasets/lothanspace/change4-tcm-dataset}
}

Please also cite the original data source:

@misc{clpds2025,
  author       = {{Ground Research and Application System of China's Lunar and Planetary Exploration Program}},
  title        = {Chang'E-4 Scientific Data},
  publisher    = {China National Space Administration},
  url          = {https://moon.bao.ac.cn}
}

License

The code and segmentation masks in this repository are licensed under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0). You are free to use, share, and adapt for non-commercial purposes with attribution.

Original Chang'E-4 imagery is owned by CLPDS/NAOC and must be downloaded directly from their portal. See docs/chinese-moon-data-access.md for their citation requirements.