This week marked the beginning of my internship at TechRealm x PreserveMy.World —
a nonprofit using AI to preserve cultural heritage sites in 3D. I'm on the Core Tech
track, focused on Platform & Web Engineering.
What is PreserveMy.World?
PreserveMy.World is a nonprofit initiative that uses AI and 3D reconstruction to
document and preserve historical sites — starting with Lahore's heritage landmarks
like Badshahi Masjid.
What I Set Up This Week
- Python, Git, GitHub CLI, and VS Code
- Gemini CLI as my AI coding assistant
- My first GitHub repo: PMW-day1
3D Reconstruction Methods I Researched
I compared five methods for reconstructing heritage sites in 3D:
1. COLMAP (Structure-from-Motion)
Takes multiple photos and produces a 3D point cloud. Great starting point for PMW.
2. NeRF (Neural Radiance Fields)
Creates photorealistic 3D scenes from images. Needs a GPU but produces stunning results.
3. Gaussian Splatting
Fast, high-quality 3D rendering — ideal for web platforms like PreserveMy.World.
4. Monocular Depth Estimation
Works from a single image or video. Most practical for field use with limited equipment.
5. Multi-View Stereo (MVS)
Dense reconstruction from multiple calibrated images. Good for building facades.
My Python Experiment
I wrote a Python script simulating monocular depth estimation and generated a depth
map output. Small experiment, but it confirmed the pipeline concept works.
What Failed
The first attempt at downloading a heritage image in Python returned a 403 error —
so I switched to a simulated depth map instead. Real-world data acquisition will need
proper API access or local images.
What's Next
I'll continue researching 3D reconstruction methods, run more experiments,
and contribute to the PreserveMy.World platform as the internship progresses.
This post is part of my TechRealm x PreserveMy.World internship journey.
GitHub: https://github.com/Anfey-SE/PMW-day1
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