ColoringMagician – Generate custom coloring pages using AI

Hacker News

Hey HN! I made ColoringMagician because I got frustrated trying to find specific coloring pages for my niece. She's a true painter, always complaining about how she'd draw it differently if it wasn't a very generic coloring page. It's built using a custom model, with some tweaks to generate clean line art (turns out, making AI create consistently good coloring pages is trickier than I thought!). The most interesting part was figuring out how to convert complex images into something that's actually colorable. Things I learnt along the way: - Kids are brutally honest beta testers - Making prompt templates is trial and error - Gemini 2.0 Flash is amazing

Visit product View on Hacker NewsFeb 19, 2025

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Launch Intel predictions

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

64%64% 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 HuntOn track for Day 1 leaderboard · Strong signals: model, gemini, using · Missing: mac, agents, macos

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

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

41%41% 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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

22%22% 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

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

Correct prediction on native model

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