Pokemon Emerald Emulator

Hacker News

Hi there, this is a toy project I worked on for the past months. It's an early stage pokemon emerald emulator. Maps, tiles, animations, warps, sprites etc. are extracted from the provided ROM file. There is a online demo [0]. After dragging a ROM file into the browser window, you can walk and explore the complete pokemon emerald world. The game engine is created only for testing purposes, you will encounter a zillion bugs. If you don't have a ROM file on hand (Attention, large GIFs): - Warps: https://i.imgur.com/pYI9ipl.gif - Behaviors: https://i.imgur.com/isgIRLD.gif - Zooming: https://i.imgur.com/GMqDYKr.gif - World Map: https://i.imgur.com/HmvBTAV.png [0] https://maierfelix.github.io/emerald-engine/static/

Visit product View on Hacker NewsNov 18, 2017

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Actual performance

4points

3comments

Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: ide, game engine, io · Missing: https docs, excited, just released

80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

16%16% 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.

Incorrect prediction on native model

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