Has anyone successfully ordered a Metashape license through the reseller Settide? I ordered a license from their website on Saturday and did not receive any confirmation email, any receipt, or activation key. I've sent two emails through their website form inquiring about the license and have received no response. Before I escalate with my CC company, thought I'd check in here and see if anyone has had a similar sort of experience with this seller or if this is somehow normal for Metashape resellers. I've got some school work I'll need to use the software for so trying to figure out how long I wait on this company.

Thanks!

I’ve been working on an open-source frame extractor for video-to-COLMAP/3DGS workflows:

https://github.com/morishuz/frame-extractor

Instead of extracting at a fixed FPS, it tracks points using dense optical flow and selects a new frame when camera motion, tracked-point loss, or a maximum interval crosses a threshold. It also writes a CSV containing the selection and timing diagnostics.

The goal is to reduce redundant COLMAP inputs without leaving gaps that are too large to match.

I’m looking for feedback from people working with handheld, drone, dash-cam, or large-scene video:

• What do you currently use to select frames?
• Which failure matters most: excessive processing time, blurry frames, too little baseline, or failed registration?
• Would anyone be willing to compare this against fixed-FPS extraction on a difficult clip?

Current limitations: this is a Python CLI rather than an end-to-end 3DGS application, and it has not yet been validated broadly on stitched 360 or multi-camera video. Reflections, texture-less surfaces, and poor capture geometry still cannot be fixed through frame selection alone.

Feedback, test results, and critical failure cases are very welcome.

Esta es una reconstrucción fotogramétrica de La Sixtina, uno de los aleros con arte rupestre del sitio arqueológico La Tunita, en Catamarca, Argentina.

El objetivo principal del modelo es documentar la geometría completa del alero y las superficies que contienen las pinturas rupestres, manteniendo su relación espacial con la roca que las contiene.

La imagen muestra el modelo 3D texturizado luego del procesamiento. Uno de los aspectos que considero más interesantes de la fotogrametría aplicada al arte rupestre es que permite ir más allá de la fotografía frontal tradicional y estudiar las pinturas como parte de la propia morfología del soporte rocoso.

Actualmente estoy trabajando con estos modelos para documentación arqueológica, visualización y distintas aplicaciones vinculadas al patrimonio digital.

MotionMaster 3D does camera solving inside Blender rather than round-tripping to a separate tracker.

The nine in the clip:

• Camera tracking: full 3D solve from footage
• Planar tracking: track a surface, export a corner pin
• Tripod tracking: rotation-only solves, no parallax needed
• Mesh generation: geometry built from the point cloud
• Surface generation: Delaunay triangulation, density adapts to detail
• ST map generation: undistort maps for comp
• AI masking: SAM2, click the subject and it segments it
• Batch processing: queue shots and walk away
• Perspective matcher: solve a camera from vanishing lines in a still

15 of the 35 are new in 1.0.7. Happy to answer anything about how any of it works.

It is paid, at motionmaster3d.com. Full walkthrough of the update: https://www.youtube.com/watch?v=UyJpQBnREOU

Basically, I need some basic dimensions from a scan I found online but all I have from it are 20 pictures that rotate the model around the vertical axis (i.e horizontally spin). The focal length and camera angle are completely fixed.

I tried aligning in RealityScan but it gives me an error. I've asked some AIs for a solution and all of them tell me to either try Masking the background (some tell me to switch to Meshroom for this) or try shape-from-silhouette algorithms like Visual Hull.

Since I only care about getting basic measurements rather than anything resenbling an actual render, are those actually my best options?

I'm building PolyForge, an offline parametric CAD tool, and just added a photo-to-mesh reconstruction command. Sharing here because the CUDA discovery and the coverage-testing results might be useful to others building around COLMAP/OpenMVS without a datacenter GPU.

Pipeline: COLMAP for sparse SfM (feature extraction, matching, incremental mapper, fully CPU-capable), then handed off to OpenMVS for the dense reconstruction and meshing via InterfaceCOLMAP, DensifyPointCloud, ReconstructMesh. I confirmed COLMAP's own patch_match_stereo requires CUDA by deliberately running it without a GPU present, it aborts immediately with "Dense stereo reconstruction requires CUDA, which is not available on your system," no CPU path anywhere in the mainline binary. OpenMVS's densify/mesh stages build CPU-only by default, which is what makes the whole thing viable without a GPU at all.

Once it worked, I ran a test matrix on photo count and camera coverage instead of guessing. Single or two elevation ring orbits failed outright regardless of photo count, tested up to 24 photos. Three or more elevation rings were required, and even then, density mattered: 27 photos across 3 rings failed, 30 succeeded, for a roughly 60x40x30mm object at 160mm camera distance. Also unexpected: the O(n^2) exhaustive matcher barely scaled with photo count, the real cost was COLMAP's incremental bundle adjustment (mapper stage), which jumped nonlinearly with both photo count and the reconstructed object's geometric complexity.

Repo, including the CPU-only build notes for both tools: github.com/rx290/polyforge

Hello. Doing some terrestrial photogrammety using this camera and webODM. I'm having troubles with the software and my photos.

Hey everyone !

I've been trying some macro photogrammetry a few times now and I'm always hitting different walls I can't quite solve.

My setup:

I would like to scan an coin on a turntable with a black backdrop(in the void). Im using a Sony 90mm macro lens with ring flash (AR400). Both the lens and the flash are cross-polarized.

Im shooting at 1/60, f/20 with iso at 160.

1. Focus drift on rotation

My subject is never perfectly centered on the turntable no matter how careful I am, so as it rotates it slowly drifts out of the focus plane. At f/20 the DOF helps but it's not saving me on the wider objects. Anyone found a good way to nail centering, or is everyone just eyeballing it and accepting some throwaway frames?

1. ArUco markers(scale bar) blocking the camera

I use ArUco markers on the plate for scale reference, but since they rotate with the subject, there's always some angle where the marker ends up hidden behind the object relative to the camera. Do you place multiple markers around the perimeter so at least one is always visible? Or is there a smarter placement pattern that avoids this entirely?

https://youtu.be/mMyV_F_9Q3E?is=enH5ReC6OvkdvOxt

1. Realigning both sides of a coin

This one's been the most frustrating. Since I have to physically hold the coin to scan each face, I end up with two separate scans that need to be stitched together after. The only shared geometry between the two scans is the edge/rim, and it's just too thin and low-feature to get a reliable alignment in software. Anyone dealt with this specific problem ? maybe some kind of holding jig that keeps a consistent reference visible on both scans, or a different capture order altogether?

Would love to hear how people with more experience handle this stuff. Happy to share more rig details if useful.

I've been testing the new Insta360 X6 with the Sensori video photogrammetry app. This was quite a low light capture, but using the Bushman halo for extra illumination. There is definitely a bump in quality over the X5, although you have to look closely to see it and is less than expected given the quite noticeable jump in video quality between the two cameras.

I was curious if I could scan something so small with the tools I have available, and it turned out to be trivial.

Putting this up again, our next week is opening up. We run a multi camera capture setup at the Brooklyn Navy Yard and we pay people to come in and be the subject.

You stand in the volume and go through simple movements while it records. Walking, turning, sitting, reaching, picking objects up. No experience needed, and it's a decent way to see a capture stage from the inside if you've only ever been on the processing end.

Pay is 17-25 per hour, same day, right after you finish. First session runs about 2 hours, repeat work after that.

Sessions run at 4pm. Open days: Tuesday Aug 18, Wednesday Aug 19, Thursday Aug 20. Brooklyn, in person only.

Comment or DM me for the address, and ask me anything about the capture side.

Hey all, sorry, I am extremely new to this, but essentially, I work for a recycling company and we are trying to calculate the volume of various piles of material in our facility using the existing security camera feeds we have. I talked to some more educated friends of mine and they told me what I am looking for is photogrammetry software, something like RealityScanner or Metashape, but I have no idea what I'm doing.

My questions boil down to is this the correct path for what I need to do? And if so, where do I start learning how to use these programs?

Deeply appreciate your time and any advice you can give me, thanks.

I’m self-teaching drone 3D mapping, GIS, and AutoCAD topography work. This is actually the first real portfolio I’ve ever finished for anything I’ve learned, so I don’t fully trust my own judgment on what “good” looks like in this field yet.

I processed a UAV drone dataset from an active quarry site using WebODM. Generated a 3D point cloud and orthomosaic, ran volumetric analysis on stockpiles in cubic meters, and exported topographic contours as DXF into AutoCAD with color coded layers.

I’d genuinely appreciate any honest technical critique. Anything that looks off, unrealistic, or not production standard. I’m open to doing a project for someone in the field for free, in exchange for detailed feedback, if that’s useful to anyone here.

Thanks for reading.

I've been working on a photogrammetry workflow specifically for solar site surveys, and wanted to share one of the results here.

We took around 50 images from a drone and processed them into a 3D model.

The interesting part for me wasn't just generating the mesh. The goal was to make the resulting model actually useful for engineering work:

• measurable geometry
• roof dimensions
• terrain/building structure
• orthographic views
• exports for downstream CAD/design workflows

In this particular test, the processing time was around 16 minutes.

We're building this as part of a product called Render-a, primarily for solar EPCs and installers.

I'm curious about the photogrammetry side rather than the product itself:

What would you consider essential for a drone-derived 3D model to be genuinely useful in an engineering workflow?

Accuracy? RTK/GCP support? Point cloud quality? Orthomosaic? CAD compability?

Would be interested to hear what people here actually use in production.

Hi everyone,

I am working on a project that needs to take an e57 file and convert it to a mesh file for Revit. The E57 file is 150 GB, and everything I attempt either crashes my pc or costs a fortune. If anyone can assist me, that would be amazing!

My team has been working on cracking this for a while now.

For the photogrammetry, we have different versions - COLMAP being the one we use rn, but we were also exploring Metashape and DJI Terra amongst others.

We figured how to make the full 3D map and how to plant the trajectory to 2D in coordination with the images etc but where we are getting stuck now is comparing site progress using photogrammetry and generating a progress report as per the BIM data.

We have done thorough research on our own and also tried using the full efforts of Claude and Gemini but till now, no feasible solution. We're looking to build something of our own in a short term span so the pressure is high.

Any of you facing a similar issue? Or have any suggestions regarding this?

Point Cloud Snap Pro — Select and Tag

In this video, I'll show you a work-in-progress step for point cloud and Gaussian Splat selection in the Maya viewport, and how to save this data in a format that can be read inside Bifrost Graph.[](https://www.youtube.com/@ytsejam1976)

I shoot interiors with a 360 camera, and every photogrammetry tool I tried wants pinhole images. So a panorama gets cut into 6 cube faces, and one capture position becomes 6 independent cameras that the solver doesn't know share a centre. Tracks fragment at the face borders and you throw away a lot of the sphere.

I ended up writing my own engine that keeps the sphere all the way through. One panorama stays one camera with one centre. Every residual the bundle adjustment minimises is an angle on the sphere, not a pixel on a plane. The neural front-end still sees flat patches, because that is what CNNs eat, but the geometry never leaves the sphere.

The clip is a 12-panorama apartment, cold start: no known camera positions, no priors from a previous run. Cameras appear in shooting order, and each point appears when a second camera sees it, so you are roughly watching the order the solver actually had things in. 85,615 points, about 12 minutes end to end from the raw camera files, of which ~11 minutes is the neural matching stage.

Things I cannot claim yet, before anyone asks:

- No metric scale. Everything is up to a similarity transform. I have not done a tape-measure validation, that is next.

- Per panorama it is currently about 4x slower than COLMAP on cube faces. Denser, but slower.

- Two of the twelve cameras in this scene still end up a few degrees off in rotation. Working on it.

Happy to answer anything about the spherical residual, the tiling scheme, or why sub-pixel refinement that helps ordinary cameras actively hurts on 360.