Luma 3D Capture vs Depth Camera RAW

Show your world in spectacular quality 3D, and share anywhere on the web. Brought to you by Luma AI. Luma is a new way to create incredible lifelike 3D with AI using your iPhone. Easily capture products, objects, landscapes, moments and scenes wherever you are. Share these fast spectacular scenes with anyone and anywhere on the web. Create cinematic product videos, impossible camera moves for TikTok. No Lidar or fancy capture equipment necessary, all you need to create is an iPhone 11 or newer. - Capture 3D scenes with intricate details, reflections, and lighting and share with everyone. Bring people where you are! - Capture products in 3D and embed them on your website exactly how they appear in real life. No more "fake 3D". - Capture 3D mesh game assets in unmatched quality and bring them to Blender, Unity or your 3D engine of choice. - Export lifelike NeRFs and Gaussian Splats to Unreal, Unity, and other supported tools. We are excited to see what you create with this brand new AI medium! If you find Luma useful, fun, or interesting, or need help please join us on Luma's Discord: lumalabs.ai/discord. When you share, please tag us on Twitter (@LumaLabsAI), LinkedIn, Instagram, or TikTok. Please Note: while Luma's 3D Viewing and Video Uploads will work on iPhone X + XR, AR Capture requires an iPhone 11 or newer.

This iOS app is designed for professional users who need to capture full-resolution depth maps using the LiDAR scanner on their iPhone or iPad. It addresses the issue of depth maps being scaled down to 8-bit when using the standard iOS libraries, allowing you to capture and save depth maps with their original precision. The LiDAR scanner on supported iPhone and iPad models provides depth information for each pixel in the captured image. However, when using the standard iOS libraries, this depth information is typically scaled down to 8-bit, losing much of the original precision. This app bypasses that limitation by directly accessing the depth data from the LiDAR scanner and saving it as a 32-bit floating-point TIFF image. Each pixel in the resulting TIFF image contains a floating-point value representing the distance from the camera to that point in the scene, in meters. For example, if a point in the scene is 5 meters away from the camera, the corresponding pixel value in the TIFF image will be 5.0. Similarly, if a point is 30 centimeters away, the pixel value will be 0.3.