API to acquire PBR materials from any portrait image for relighting

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With SwitchLight API, you can extract surface normal map, albedo map, roughness map & remove background of any portrait image and use it in your own 3D pipeline that supports physical-based-rendering (PBR). 1. Surface Normal API: Surface Normal maps represent in which direction each pixel is pointing towards in 3D space, and without surface normal, things will look super flat and unrealistic. 2. Albedo API: Albedo map removes any shadows or highlights from the original image and represents what the subject would look like under very flat white lighting. Also known as diffuse map or base color. 3. Roughness API: Roughness map represents how rough or smooth the surface is. The darker it is, the smoother the surface is like a mirror. For example your clothes is much rougher than your skin, and will be represented brighter in the roughness map. Also known as glossiness map. 4. Background Removal: Removes the background and return PNG file with alpha channel Below is a video of a demo app where you can relight a human portrait in realtime using SwitchLight API & ThreeJS. Here, I extracted surface normal, albedo and roughness map using SwitchLight API and and used ThreeJS's Physical Based Rendering capability. We've also attached a sample code snippet so feel free to try it out! Demo Video: https://www.youtube.com/watch?v=JaIBwL4w7HA Code Snippet: https://www.switchlight-api.beeble.ai/docs/tutorial

Visit product View on Hacker NewsAug 15, 2023

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52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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