Made a tool to restyle or design your room

Hacker News

When I was looking to spruce up my office, the only options available were expensive interior design services. I just wanted to quickly get some ideas without breaking the bank. So we made a new tool to do exactly that. You can add an image of your existing room or even a mockup/drawing, give it a style, and it'll generate some ideas for you. I know a few of these have popped up, but I found them to be really bad at restyling rooms. Ours isn't perfect and there are lot of improvements to make, but some of the outputs are stunning (IMO) and it does a decent job at following the room's existing layout and dimensions. For my use case - it's almost perfect! I'd love to get your feedback. To access: 1. Go to https://shopdeft.com 2. Click the little image icon in the middle of the search bar. 3. We require an account (email/pass). It's free for now. 4. Upload a picture or generate something from scratch. Notes: - If you need help finding the button to generate, here's a screenshot: https://imgur.com/a/I109Na8 I know this isn't intuitive at all, but we just launched it. Apologies! - There is a bug with uploaded images above 3mb. If it's spinning longer than 30 seconds, that's likely why. Downsize the image and it should work. ------ Here are some before & afters - https://imgur.com/a/svBJsYE

Visit product View on Hacker NewsJan 12, 2024

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

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

64%64% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, email, notes · Missing: mac, agents, macos

49%49% predicted probability of success on Product Hunt, 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.

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

12%12% 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.

Incorrect prediction on native model

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