SwitchLight – Relighting AI in the Browser

Hacker News

Hoon Kim here. SwitchLight is an AI VFX editor that enables filmmakers to completely change lighting after the shot was taken. SwitchLight works by the user loading an image/video and then selecting a background. Our AI removes the actor from their original background and composite them into the new background while simultaneously relighting them correctly to reflect their new environment. The final result is pixel-accurate with realistic shadows and highlights. Users also have full access to intermediate passes (normal, albedo, depth, roughness) for their custom use case and controllability. We initially launched SwitchLight for casual users (selfies, headshots, etc.), but most heavily engaged users were professionals from VFX industry. As a result, we pivoted towards a more professional industry and we are preparing a Desktop app and Nuke Plugins (with unlimited number of inferences). Sorry for the forced login. We have limited GPU resource, so we had to limit total number of inferences per user. We're eager to hear your thoughts and feedback!

Visit product View on Hacker NewsJul 14, 2023

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

86%86% 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: user, new · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, users · Missing: mobile apps, ios, personal

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 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

44%44% 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

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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