Overlay map tiles onto Autodesk's 3D BIM Viewer

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https://github.com/infra-plan/bim-tile-overlay We manage infrastructure using BIM models in Autodesk Viewer. We needed to show aerial imagery and street maps underneath the 3D models, synced to the camera in real-time, so that we can give some context to the shown infrastructure. The hard part: coordinate transforms. A Revit model's internal coordinates are in feet, rotated, translated, and offset from a local CRS projection, which itself needs to be converted from WGS84. The library ray-casts the camera frustum onto a ground plane, converts the hit points to lon/lat, determines which XYZ tiles to fetch, stitches them into a canvas, and maps the result onto a THREE.js plane, all updating on camera change. ~500 lines of JavaScript, MIT license, one peer dependency (proj4). We would love to hear community feedback! The reason we decided to open-source is quite common: we couldn't find something similar to this that would not require a significant change to our workflow. Hope others will find benefit from this library.

Visit product View on Hacker NewsMar 24, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, context · Missing: mac, agents, macos

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

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BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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