This is the Linux app named Map-Anything whose latest release can be downloaded as map-anythingsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Map-Anything with OnWorks for free.
Volg deze instructies om deze app uit te voeren:
- 1. Download deze applicatie op uw pc.
- 2. Voer in onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX in met de gebruikersnaam die u wilt.
- 3. Upload deze applicatie in zo'n bestandsbeheerder.
- 4. Start de OnWorks Linux online of Windows online emulator of MACOS online emulator vanaf deze website.
- 5. Ga vanuit het OnWorks Linux-besturingssysteem dat u zojuist hebt gestart naar onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX met de gewenste gebruikersnaam.
- 6. Download de applicatie, installeer hem en voer hem uit.
SCREENSHOTS
Ad
Kaart-Alles
PRODUCTBESCHRIJVING
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses, sparse or dense depth) and produces a rich set of outputs including per-pixel 3D points, camera intrinsics, camera poses, ray directions, confidence maps, and validity masks. Its inference path is fully feed-forward with optional mixed-precision and memory-efficient modes, making it practical to scale to long image sequences while keeping latency predictable.
Kenmerken
- One feed-forward transformer that covers >10 reconstruction tasks
- Multi-modal inputs (images, calibration, poses, depth) with unified APIs
- Dense metric outputs: 3D points, depth (z and along-ray), intrinsics, poses, ray directions, confidence and masks
- Turnkey demos plus exporters to COLMAP and Gaussian splatting pipelines
- Mixed-precision and memory-efficient inference for long sequences
- Modular “building blocks” (UniCeption, WAI) to scale data and models
Programmeertaal
Python
Categorieën
This is an application that can also be fetched from https://sourceforge.net/projects/map-anything.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.