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gl

glTF files can be converted to HTML5

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glTF files can be converted to HTML5

First check that our 3d engine is compatible with the 3d model. Then upload the model to hosting space and pass an url to gltf to html5 zip converter. Choose "transparent canvas" and press "convert to html5". In response, you'll receive a new zip file containing our 3d engine and your specified 3d model integrated together. Unzip the zip to directory in your hosting space, and add <embed src="dir/index.html" width=640" height="480"/> and you're all done. Check your .htaccess based on our faq and point your browser to your web page. And you'll see 3d model displayed correctly in your own web page.

Visit productView on Hacker NewsJul 17, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
31%31% 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
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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