Custom coloring pages for kids and adults

Hacker News

I built colorbliss.art back in September basically so that I could spend less time scrolling on google looking for coloring pages. A typical scrolling session with my five year old would be: Him: "Dad, can I have a coloring page" Me: "Sure, what kind do you want" Him: "Something with dinosaurs, and maybe spiderman" Me: "I'm not sure if we're going to find that" Him: "Just look it up dad" Me: "Ok...hm, I"m not finding that" Him: "Just keep scrolling dad" Me: scrolling, scrolling Him: "Just keep scrolling dad" *repeat forever* I thought this would be a great use case for AI - creating the actual coloring sheet he wanted. It takes a text prompt (Spiderman at the Eiffel Tower, Skeletons on parade) and makes a coloring page in about 10s or less. We've had a lot of fun using it together, and so I thought I'd share it here as well. Would love any feedback!

Visit product View on Hacker NewsJan 30, 2024

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

62%62% 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.

Product HuntUnlikely to reach the leaderboard · Strong signals: google, using · Missing: mac, agents, macos

49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

31%31% 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 · Strong signals: google, para · Missing: mobile apps, ios, personal

26%26% 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

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

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

Correct prediction on native model

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