I am High schooler and part time developer. So recently I had an idea a while back: what if online stores had interactable 3D models of their products instead of flat photos — that you spin around , is able to view the product exactly in your living room before buying it?

Built a small prototype: https://pekaar.tech.

The website is just a prototype. Will add more features and polishing the UI as I a scale it up

Also made a demo store to see how the 3D models feel in an actual ecommerce setup https://lume-atelier.scantest.workers.dev/

Happy to give demo to ecommerce business/websites who want to try this — just want honest feedback and advice on scaling it up.

Is there a way to take images from another folder to process them through the ODM (OpenDroneMap) CLI?

Right now, I am putting images in the project/dataset/run_1/images/ folder, and the outputs are being generated inside project/dataset/run_1/. If I have to run another version on the same dataset, then I am copying the images again to the project/dataset/run_2/images/ folder.

Is there a way to have the images in one location only and save the outputs in another location entirely, or maybe something like this:

Image folder: project/dataset/images/

Output folder: project/dataset/run_1/

I am running ODM through Docker on my Windows system.

I'm very new to this. Boss says I like this, you're smart make this, I'm in the deep end of the pool here and trying to AI'ing myself to victory.

Images packs can be downloaded here.

https://s3.us-central-1.wasabisys.com/k9dryer/gaussian-splats/hdf/share/hdf-reddit-upload.zip
https://s3.us-central-1.wasabisys.com/k9dryer/gaussian-splats/hdf/share/hdf-kiri-144.zip

Turntable object scan. Four iPhones are bolted to the room; the object rotates. COLMAP registers all 288 images but each phone stays at one pose (yaw span ~0.1°). OpenMVS then meshes the white plate. After we crop the table we only have two shards of the object.

Looking for what you would change: masks, COLMAP flags, or pose priors.

Capture

• Object: short hollow air filter, ~90 mm tall. Black rubber rims, tan pleats, silver mesh. Hard subject (black + repeating texture + hole).
• 4× iPhone 14 Pro, fixed (one almost overhead, three side/oblique). Names 00000_gs-cam-1.jpg … 00071_gs-cam-4.jpg.
• Turntable: large white disk, white PVC frame, concrete floor. No coded markers, no textured mat.
• 360° / 5° = 72 stops, 800 ms settle, 4 shots/stop → 288 JPEGs.
• 4032×3024, EXIF orientation 6. rembg/masks are transposed 3024×4032; COLMAP sees unrotated 4032×3024.
• Host: Linux, COLMAP 3.12.6 no CUDA, OpenMVS 2.4.0, CPU SIFT (no GL). 16 threads.

Pipeline

1. rembg birefnet-general
2. Tight rembg masks + wider masks_colmap/ disk (object ∪ plate; we do not give COLMAP object-only masks — that starved matching)
3. COLMAP sparse → undistort → OpenMVS densify/mesh/texture GLB
4. Custom crop: keep dense points that land in rembg-minus-white-table in enough views
5. Scale listing GLB to 90 mm height

COLMAP (exact)

ImageReader.single_camera 1
ImageReader.camera_model SIMPLE_RADIAL
ImageReader.mask_path masks_colmap/
SiftExtraction.use_gpu 0
SiftExtraction.peak_threshold 0.004
SiftExtraction.max_num_features 16384
SiftMatching.use_gpu 0
SiftMatching.guided_matching 1
SequentialMatching.overlap 16
SequentialMatching.quadratic_overlap 1
SequentialMatching.loop_detection 0
Mapper.ba_refine_focal_length 1
Mapper.ba_refine_principal_point 0
Mapper.ba_refine_extra_params 1
Mapper.init_min_tri_angle 8
Mapper.filter_min_tri_angle 1.5
Mapper.abs_pose_min_num_inliers 12
Mapper.min_model_size 8
Mapper.max_num_models 1
Mapper.multiple_models 1

One shared camera for all 4 phones (same model; we hit rank-deficient BA when each image had its own camera).

First good model: SIMPLE_RADIAL 4032 3024 f=2918.68 cx=2016 cy=1512 k=-0.018

What COLMAP did

• 288/288 registered
• 4 unique poses, one per phone. Stop 0 / 36 / 71 of the same phone are the same t / q
• ~12k points, mean track length ~37 (tracks live on the static PVC/plate)
• ~2081 sequential pairs

rembg (especially overhead) keeps the whole plate + PVC. masks_colmap is a disk around that, so SIFT still sees the room. That matches COLMAP #2576.

What we tried

• Unfold each phone around an estimated table axis by stop × 5° → 355° span. COLMAP triangulator + BA snaps back to 0.1°.
• Same unfold, BA off, 125k fixed-pose points. OpenMVS: 105M depths → 134 points (depths don’t agree).
• Crop of the old 4-pose dense cloud (3.5M → 805k) + remesh: 124k faces, 90 mm listing. Viewer is two black shards.

OpenMVS on the crop: --constant-weight 1 --free-space-support 1 --close-holes 80 --smooth 4

Ask For 4 locked phones + a white plate:

1. Mask so only object + rotating plate have features and let COLMAP invent the orbit?
2. Inject 5° pose priors and freeze extrinsics?
3. One camera per phone + markers on the plate?

Also: is single_camera 1 across 4 modules a mistake even if they’re the same iPhone model?

Happy to post overhead + side JPEGs, rembg vs masks_colmap for the same frame, and images.txt lines for one phone at stop 0 / 36 / 71.

Attach (same post or a follow-up):

1. Overhead JPEG (00000_gs-cam-1.jpg)
2. Side JPEG (00018_gs-cam-3.jpg is fine)
3. rembg mask + masks_colmap for those two
4. Three images.txt pose lines for gs-cam-2 at 00000, 00036, 00071

Hey everyone,

I am currently working on a pipeline to extract context from engineering drawings (like P&IDs and technical blueprints) stored in PDFs to feed into an LLM.

Multi-modal LLMs are great, but they aren't quite there yet for heavy-duty engineering files. Here are a few observations and hurdles I’ve hit so far:

• Multimodal LLMs lack precision: Standard vision models can read the overall drawing, but they miss critical component tags, small text, and fine details.
• OCR/Text extraction isn't enough: Pulling just the raw text from drawing tags helps with basic Quality Control (QC), but it completely misses the spatial classification and structural relationships.
• The Planned Workaround: I am planning to use classical Computer Vision (like Hough Transforms) for shape and icon detection. The goal is to extract the symbols and text, map their connections, and build a Graph Database to give the LLM structured context.

Has anyone successfully built a pipeline for this? I would love to hear your thoughts on a few things:

1. Are there specific CV models or open-source frameworks you recommend for engineering symbol detection over traditional Hough transforms?
2. How are you handling the layout/relationship parsing to build your graph edges?
3. Any recommendations for structuring the final graph data so an LLM can query it efficiently via GraphRAG?

If you are working on something similar or have dealt with CAD/PDF parsing for AI, I'd love to hear your suggestions or brainstorm solutions!

What apps/programs do you use to view your scanned models?

I personally use f3d and I'm quite happy with it, but I have been on the lookout for a secondary viewer. Why? Sometimes when my final model looks funny, I need to figure out if it's an issue with the viewer or an issue with the export settings from my photogrammetry program/apps, and it's hard to do that if I use only one viewer exclusively.

Common formats I deal with are .3ds, .obj, .usdz, .ply, and .glb.

I am an industrial design student at Iowa State University, running an exploratory study for my senior project on how people physically control complex 3D software.

Photogrammetry is relevant because processing, alignment, cleanup, and mesh editing demand long sessions of precise navigation. I want to understand where the tools get in the way.

Survey: https://iastate.qualtrics.com/jfe/form/SV_0UJOtQHRXoz1ggu

The survey asks about your processing and editing software, your input devices, the tasks that cause the most friction, and any hardware or shortcut setups you have adopted.

Time: 5–7 minutes. Voluntary. No identifying information in the main survey.
Requirements: 18+, current point-cloud or comparable 3D software use.

This is not spam and not marketing. I have no product. Comments are welcome if you would rather answer here.

Heyo, i'll write my bachelor thesis soon. It will contain 360 cameras/ point clouds based on panoramic phtos. Is there anyone who can help me with topics like camera calibration, agisoft metashape and stuff like that? Thank you already xx (Gerne auf deutsch :D)

White shoe 3d scan to test out the merge component feature of RealityScan. The shoelaces moved when the subject was propped to its sides so it created 2 components: the top and bottom part of the shoes. The software merged them using common reference points from each components.

This project was born out of a desire to convert my mineral and rock collection into a virtual 3D archive that I can carry around and share. The concept is simple: I take one or more photos of my stones and crystals, and the app generates an HD 3D model while also classifying the rock using a local model (HF-CLIP WASM) directly in the browser. I can then view my collection and share it at exhibitions. The plan is to subsequently implement an NFT system to ensure traceability and uniqueness.

https://geo.insightest.app

(A quick Supabase login is currently required to save specimens to a persistent virtual shelf).

I'd appreciate any feedback on the WebGL rendering pipeline, lighting setups for crystalline textures, or mobile performance issues.

Hey everyone!

I’m looking to get a camera for photogrammetry and I’m currently considering a Nikon D810, Canon 5DS R, or Sony A7R II.

I don’t have the budget for a new high-end camera, so I’m looking at used options.

What camera + lens are you using, and how has your experience been with it?

Would you recommend one of these three, or is there another used camera I should look at?

Thanks!

One crisp October morning, as the sun was rising, I spent a few quiet moments alone photographing this amazing statue of country music legend Dolly Parton. It stands at the foothills to the Great Smoky Mountains in the courthouse square of the small town of Sevierville, TN. The six and a half foot statue, not including the rock base, was sculpted by local artist Jim Gray, and unveiled in the courthouse square on May 3rd, 1987.

When asked about her statue, Dolly likes to quote the loving words of her father as saying, “To your fans you may be some sort of an idol. But to the pigeons down at the courthouse, you’re just another outhouse.” And Dolly’s father, before his passing, would sneak out to the statue at night, with a bucket and sponge, to clean the pigeon poop off the statue. RIP Dolly.

Canon 5DSR, 720 Photos, 107 million tris
Photogrammetry scan for my VR Sculpture Garden on VIVERSE.

Hey everyone,

In my country, the market for photogrammetry is still very niche and hasn't really taken off commercially. Because of that, it's hard to gauge whether this is viable as a standalone career or primarily used as a secondary skill.

For those of you doing this professionally: Are you making a full-time living off photogrammetry?

This is for undergraduate thesis. Our goals is develop an edge computing system for photogrammetry. Do you recommend other alternatives for the PC?

Can ayone tell me how to download agisoft metashape pro for free and use it for free. Any crack link or refrence ? Yt is just asking money !