Stable Diffusion print-on-demand apparel

Hacker News

Hey HN, Obviously we are experiencing a surge of stable-diffusion based apps at the moment, but I have yet to see anyone try and map the outputs onto actual physical products that can be delivered to your door. I wanted to make it easy to: - pick an artistic style - hit 'record' and speak into your phone / tablet / desktop or whatever, and describe the kind of design you want your clothing to have (since speaking is more spontaneous that typing) - swipe among a variety of mockups (t-shirts, hoodies etc.) featuring your design, and order it to your door with the click of a button The product is called 1SEWN. Fulfilment is currently achieved using a print-on-demand service called Printful ( https://www.printful.com ) that I have integrated with. If you guys would like to try it, I would love some feedback. Shipping is currently limited to outside Europe, but even if you are in Europe, your feedback about the whole UX would be much appreciated! Much love, Matt

Visit product View on Hacker NewsNov 5, 2022

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

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, physical, using · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

16%16% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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