Datasets:
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Original files here
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pds4-tools>=1.3
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colour-demosaicing>=0.2
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colour-science>=0.4
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scikit-image>=0.21
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Pillow>=10.0
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numpy>=1.24
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Chang'E-4 TCM Dataset
Tools and data for terrain classification using 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
# Convert PDS files to images
python scripts/convert_pds.py data/raw data/images
Downloading Chang'E-4 Data
Data is available from China's Lunar and Planetary Data System (CLPDS).
1. Register an Account
- Go to https://clpds.bao.ac.cn
- Create an account (check spam folder for confirmation email from NAOC)
2. Download Data
- Navigate to Chang'E-4 data search: https://clpds.bao.ac.cn/ce5web/searchOrder-ce4En.do
- Select an instrument:
- PCAM - Panoramic Camera (rover, stereo pairs)
- TCAM - Terrain Camera (lander)
- LPR - Lunar Penetrating Radar
- VNIS - Visible/Near-IR Spectrometer
- Choose data level (L2A or higher for calibrated data)
- Add files to cart and process order
- 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
- Read PDS4 file using
pds4_tools - Debayer raw Bayer images (PCAM full-resolution)
- Apply 2% linear contrast stretch
- Save as PNG
Project Structure
βββ data/
β βββ masks/ # Segmentation mask annotations (JSON)
β βββ raw/ # Downloaded PDS4 files (you provide)
β βββ images/ # Converted PNG images (generated)
βββ docs/
β βββ chinese-moon-data-access.md
βββ scripts/
β βββ convert_pds.py
βββ requirements.txt
References
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.
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