> The platform is designed according to a minimalist visual philosophy: black and white, free of decorative elements, with no animations or unnecessary graphics.
I'd remove the half page autoplaying "video" on the top of the landing page in that case.
Photogrammetry & image processing, anything to do with dimension reduction (basically every field with real-world sensor data), ontology/semantic data processing...
Shameless plug: I'm working on a project in this space (see my other comment on this post), I'd love to hear about your prefered workflow for ingesting 3d data into your editor.
Put another way, what output formats are most convenient for your use case? Are raw point clouds (XYZRGB) useful to you for eg. "prototyping volumes" or do you require meshes as a starting point? If the latter, how would you quantify how much retouching is acceptable (holes, suboptimal meshing, irregularities...) for an urban model?
If you'll allow a shameless plug: I'm about to publish a python package to help doing just that, by combining photogrammetric projects.
The workflow is take a couple hundred overlapping pictures, compute a model using an existing backend and store the image/3d data. Rinse and repeat. When you have a few neighbouring projects, we recompute submodels at the boundary and merge the involved 3d models by reprojection.
Currently wrangling some issues around packaging, a BSD licensed functional prototype should be out sometime next week.
I'd love to get some users or eyes on it, do get in touch!
Plus tor hidden services -or whatever the current nomenclature is- offer a fairly robust and painless story for authentication in this "sorta VPN" scenario. Generate a couple extra keys and invite a friend and his bots.
With pleasure, drop me a mail and I'll get back to you next week (last three letters of my username here @ rest of my username dot artificial intelligence).
I haven't put anything online yet though sorry!
I'm working on a collaborative photogrammetry solution (think async/distributed 3d mapping from overlapping pictures) that shares data via IPFS.
Flattering myself heavily, I believe this sort of public-data consuming application fits like nothing else.
I actually got into software/systems engineering working on internal software for "minor" player groups in EVE. The level of integration[0] those orgs had 10+ years ago outranks 80% of my current real-world clients in terms of discoverability, documentation and depth.
I mean that's what you get from a bunch of eve-playing nerds committing to a labor of love. Best projects I've ever had.
[0] Real time updating mining & trading boards by location, 100bn+ ISK inventory tracking down to the cent across many corps, characters, inventories & contracts, ... Killboard & market data feeds, risk evaluation, resource allocation optimisers... Absolutely impeccable archives & backups going back 5+ years, on top of postgres & flask iirc.
edit: And audit logs EVERYWHERE. Seriously, I've seen better CYA/KYC/chain of responsabilities from eve recruitment corps than some actual for profit entities.
That's a good point, but it does raise the question of how best to transmit notes or information with anyone who stumbles on the repo.
I understand these platform-specific features to be a way to show you do your homework and can integrate third party tooling or workflows into your own things.
Your points make sense and they're on The Checklist, thanks! I probably won't sweat CI/CD integration for the demo yet but ship (as the other commenter mentionned, also thanks!) something readable, mostly testable and usable (but limited) on day 0 and go from there.
I do wonder what a recruiter looks for in a good README though. Technical chops or perspective on potential applications/intended project direction or ... ?
Could you list some things that are red/green flags when perusing someone's public code/projects?
I'm preparing to publicly release a project with the intent of building it up to demonstrate my own experience level.
I'm asking as someone with next to no prior public code despite developping back-end almost full time since I dropped out 10ish years ago.
I guess I'm asking for external criteria for whether I'm impostor-syndroming!
I've been toying around with photogrammetrically matching in-flight bird silhouettes in order to have a plantnetlike bird classifier.
Very much in the data acquisition stage but I'm seeing moderate success in clustering images by bird shape so far. In between other photogrammetry work I'm starting to think about how to use colour information and reading up on how to select and train a ML model for this problem.
Sounds like it could. The logistical pipeline for advanced industries used to be... Intricate.
And usually depended on exploiting "gig economy" miners at the bottom, come to think of it.
Hi, I'm currently working on a project in that area. The main workflow in the system is take a bunch of pictures, SIFT & match them, then generate a sparse model of 2d features (image coords), 3d features (point cloud in relative coords) and camera positions. We then shard and re-combine different models to synthesize larger or more precise reconstructions.
I'm building with clojurescript & Three.js[0] in the frontend, and can recommend the stack
Back to your comment I'd love to hear what you're looking to do and what you'd need, sounds like I may have explored the same problem space.
I'd remove the half page autoplaying "video" on the top of the landing page in that case.