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AnySelfie – AI Art Seflies for the Masses

Hacker News

AnySelfie – AI Art Seflies for the Masses

Howdy HN! I had a lot of fun putting myself into different universes (Apollo 11, Hulk, Wild West, Dr Strange) using Dreambooth and Stable Diffusion. I'm curious to see if there is an appetite for this type of entertainment app. My vision is pre-configured prompts and pre-generating images, so people can explore it like a selfieverse feed. For technical users, I would offer them to download the 2GB model so that can own it and run their own prompts. Long term, maybe open up the prompt UI for technical users. Another goal was to re-learn Rust. This UI is built in Yew (Rust, CSS, and HTML only) and the backend is in Actix. It has been a great practical project for getting practice with the language. Thank you for the feedback!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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, user, using · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
29%29% 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
19%19% 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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