Datasets:

uva-cv-lab
/

dynamic-real-estate-10k

dynamic_re10k_part001.tar.gz    # Archive chunk 1
dynamic_re10k_part002.tar.gz    # Archive chunk 2
...
dynamic_re10k_partXXX.tar.gz    # Archive chunk N
dynamic_re10k_manifest.json     # Manifest with checksums (IMPORTANT!)

⚠️ IMPORTANT: Download ALL files including dynamic_re10k_manifest.json

🔓 Extraction Methods

Method 1: Automated Extraction with Verification (Recommended)

Prerequisites: Python 3.7+

Download the extraction script:

wget https://raw.githubusercontent.com/YOUR_REPO/scripts/extract_split_archives.py

Extract and verify:

python extract_split_archives.py \
  --archives-dir . \
  --output-dir ./dynamic_re10k \
  --manifest ./dynamic_re10k_manifest.json

What it does:

✅ Verifies MD5 checksums for all archives
✅ Detects missing or corrupted files
✅ Extracts all archives to output directory
✅ Validates extraction

Method 2: Manual Extraction

Extract all archives (Linux/Mac):

for f in dynamic_re10k_part*.tar.gz; do
    echo "Extracting $f..."
    tar -xzf "$f"
done

Extract all archives (Windows PowerShell):

Get-ChildItem dynamic_re10k_part*.tar.gz | ForEach-Object {
    Write-Host "Extracting $_..."
    tar -xzf $_.Name
}

Extract single archive:

tar -xzf dynamic_re10k_part001.tar.gz

✅ Verify Integrity (After Extraction)

Check Manifest

# View manifest
cat dynamic_re10k_manifest.json

# The manifest contains:
# - Number of chunks
# - MD5 checksums for each archive
# - File counts and sizes

Verify Checksums (Linux/Mac)

# Create checksum verification
for chunk in $(jq -r '.chunks[].filename' dynamic_re10k_manifest.json); do
    expected_md5=$(jq -r ".chunks[] | select(.filename==\"$chunk\") | .md5" dynamic_re10k_manifest.json)
    actual_md5=$(md5sum "$chunk" | cut -d' ' -f1)
    
    if [ "$expected_md5" = "$actual_md5" ]; then
        echo "✓ $chunk"
    else
        echo "✗ $chunk (checksum mismatch!)"
    fi
done

Verify Checksums (Python)

import json
import hashlib
from pathlib import Path

def verify_md5(file_path):
    hash_md5 = hashlib.md5()
    with open(file_path, "rb") as f:
        for chunk in iter(lambda: f.read(4096), b""):
            hash_md5.update(chunk)
    return hash_md5.hexdigest()

# Load manifest
with open('dynamic_re10k_manifest.json', 'r') as f:
    manifest = json.load(f)

# Verify each chunk
for chunk in manifest['chunks']:
    filename = chunk['filename']
    expected = chunk['md5']
    actual = verify_md5(filename)
    
    if expected == actual:
        print(f"✓ {filename}")
    else:
        print(f"✗ {filename} - Checksum mismatch!")

📁 Expected Directory Structure (After Extraction)

dynamic_re10k/
├── train/
│   ├── images/
│   │   ├── scene1_clip0000/
│   │   │   ├── 00000.png
│   │   │   ├── 00001.png
│   │   │   └── ...
│   │   ├── scene1_clip0001/
│   │   └── ...
│   ├── metadata/
│   │   ├── scene1_clip0000.json
│   │   ├── scene1_clip0001.json
│   │   └── ...
│   ├── videos/
│   │   ├── scene1_clip0000.mp4
│   │   ├── scene1_clip0001.mp4
│   │   └── ...
│   └── full_list.txt
├── test/
│   ├── images/
│   ├── metadata/
│   ├── videos/
│   └── full_list.txt
├── test_scenes_info.json
└── test_scenes.json

📋 Dataset Information

Train Split

Scenes: ~3,900+ clips
Frames per clip: 20-40 frames
Total frames: ~160,000+
Format: 1080x1080 PNG (center-cropped)

Test Split

Scenes: ~77 clips
Frames per clip: 20-40 frames
Total frames: ~3,000+
Format: 1080x1080 PNG (center-cropped)

Metadata Format (JSON)

Each scene has a metadata JSON file containing:

{
  "scene_name": "scene_clip0000",
  "source_video": "scene_name",
  "original_frame_range": [0, 39],
  "num_original_frames": 40,
  "num_kept_frames": 40,
  "frames": [
    {
      "frame_idx": 0,
      "original_frame_idx": 0,
      "image_path": "/absolute/path/to/00000.png",
      "fxfycxcy": [fx, fy, cx, cy],
      "w2c": [[...], [...], [...], [...]]
    },
    ...
  ]
}

🚀 Quick Start

# 1. Download all archives and manifest

# 2. Extract all
for f in dynamic_re10k_part*.tar.gz; do tar -xzf "$f"; done

# 3. Verify structure
ls -la dynamic_re10k/train/images/ | head -20
ls -la dynamic_re10k/test/images/ | head -20

# 4. Check train/test lists
wc -l dynamic_re10k/train/full_list.txt
wc -l dynamic_re10k/test/full_list.txt

💾 Storage Requirements

Compressed (archives): ~20-30 GB
Extracted: ~45-50 GB
Total required (for extraction): ~70-80 GB

Make sure you have enough disk space before extraction!

🐛 Troubleshooting

"Archive is corrupted"

Re-download the specific archive
Verify MD5 checksum matches manifest
Ensure download completed fully

"Missing files after extraction"

Check if all archives were extracted
Verify all archives were downloaded
Check disk space

"tar: command not found" (Windows)

Install Git for Windows (includes tar)
Or use 7-Zip to extract .tar.gz files
Or use WSL (Windows Subsystem for Linux)

"Disk space full"

Archives + extracted need ~70-80 GB
Delete archives after successful extraction to save space

📝 Citation

If you use this dataset, please cite:

📧 Support

For issues or questions:

Open an issue on GitHub
Check the Hugging Face dataset page
Contact: xuweic@email.virginia.edu

📜 License

[Specify your license here]

Last Updated: 2025-10 Version: 1.0