Dimidium – Crafting Terminal color scheme with color science

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Dimidium is a standard-looking terminal color scheme. All colors have been adjusted to have fine visibility. Crafted with Color Appearance Model, it considers the perceptual aspects(lightness, hue) of human color vision. It aims to be a decent default for terminals. Preview, Download: https://github.com/dofuuz/dimidium Detailed explaination how I made the color scheme: https://dofuuz.github.io/color/2024/03/17/dimidium-terminal-... The code used to make color scheme is also present in the repository.

Visit product View on Hacker NewsApr 18, 2024

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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, code, plain · 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

37%37% 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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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