Recreate Images with Emojis

Hacker News

This demo allows you to recreate images using emojis. You can provide images or emojis to paint with, and it will attempt to recreate images using emojis. Much of the code is adopted from the Paint Transformer ( https://arxiv.org/abs/2108.03798 ) paper. In this code base, I treat emojis like “brushes”, and use a Gumbel Softmax-based lookup to choose an emoji to paste to the canvas during training (similar to how attention uses a softmax to select keys during training).

Visit product View on Hacker NewsMay 23, 2024

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

45%45% 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 · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

17%17% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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