Earlier quoted context omitted.
That's not an assertion I'm going to take seriously without evidence.
[flagged]
Link the evidence, then. Numbers, not vibes.
Map Features in OpenStreetMap with Computer Vision
101–108 of 108 posts
Re: Map Features in OpenStreetMap with Computer Vision
#102Experiencing automated mapping first-hand makes me extremely wary of it. I've travelled across South America on a motorcycle, and OSM has a large amount of edits there that look automated (particularly in Brazil), making it barely usable in certain places. I'm not even talking about rural roads but also fairly large cities.
Hi. Just out curiosity: where in Brazil?
Re: Map Features in OpenStreetMap with Computer Vision
#103Hello everyone, thanks for all the valuable feedback.
I have published a new release where any code to directly upload to OSM has been replaced with an export to OsmChange format.
I hope this is a step in the right direction, I will continue the discussion on the dedicated thread in the OSM forum.
Re: Map Features in OpenStreetMap with Computer Vision
#104Id love to see a bit more detail on fine tuning SAM/2 to do things like detect pools or solar arrays. Both these are fantastic things to have mapped for community resilience projects, but I've not been able to follow along with SAM2 fine tuning at all. I've got a Yolov8 model which does quite a good job of finding and segmenting out solar, but the edges are absolutely horrible and require an insane amount t of work t…
> but I've not been able to follow along with SAM2 fine tuning at all.
Hi there! There is no SAM2 finetuning involved in the project. The segmentation data from OSM doesn't have enough quality to properly train a segmentation model from it.
What I am using here is a YOLO model for bounding box prediction. The bounding boxes from OSM are good enough for this. I then pass the each individual bounding box as a "prompt" to SAM2 for a segmentation of what is inside.
I also tried to pass the centroid of the box as a "prompt" for SAM but it gave worse results.
Re: Map Features in OpenStreetMap with Computer Vision
#105Wait, we are not mapping things we see in sattelite images, we are mapping things that have ground truth. Please do not contribute anything ai-fantasized
Satelite images are the ground truth OSM is traced on. And the quality of those tracings varies wildly at times, I've had to fix weirdly offset shores that had roads on them placed on the sea on more than one occasion. If this can be somewhat consistent then it'll probably do better than the average OSM contributor. Something like segmenting houses, roads, bodies of water, comparing against current data and highlight…
> Something like segmenting houses, roads, bodies of water, comparing against current data and highlighting inconsistencies for correction would be a good start though.
Hi there, I agree that is a valuable usage of a model trained with OSM data.
I didn't have the time to release the code but I am/was doing exactly that to refine the training dataset. I take the trained model and run it against the ground truth from OSM. Any heavy mismatch between the two almost always result in an useful edit to be made in OSM.
Re: Map Features in OpenStreetMap with Computer Vision
#106Hi from the OpenStreetMap Foundation. Please don't add AI-detected features directly to the database. The algorithms have problems with false positives, and with mapping straight or rectangular objects as wobbly, as shown in the second-to-last screenshot. As a helper to detect missing features, this is a precious tool. But we still need human intervention to make sure the detected objects are drawn correctly. See als…
Replied to daavoo, can I suggest adding a tag for ML originated features? As other comments have stated, it is likely that these tools are already being used (potentially semi-automatically) and this could help prevent them from polluting the DB wholesale.
Hi there! Feel free to jump into https://community.openstreetmap.org/t/about-mapping-features... , I think is a good point to discuss.
Re: Map Features in OpenStreetMap with Computer Vision
#107Hi from the OpenStreetMap Foundation. Please don't add AI-detected features directly to the database. The algorithms have problems with false positives, and with mapping straight or rectangular objects as wobbly, as shown in the second-to-last screenshot. As a helper to detect missing features, this is a precious tool. But we still need human intervention to make sure the detected objects are drawn correctly. See als…
> But we still need human intervention to make sure the detected objects are drawn correctly. Hi, I am the author. The demo app and any provided code example includes a step asking a human to verify the detected features. You can't upload them automatically unless you modify the source code. I reiterate the human verification across the docs, linked post, and any code samples. I haven't ever uploaded features automat…
I know at this point it's almost one of Mozilla's mottos to be horrible at communication but how come nobody felt the need to maybe talk about stuff like this before publishing it?
Re: Map Features in OpenStreetMap with Computer Vision
#108Earlier quoted context omitted.
This is an amazing set of resources, thanks for sharing. I have been tinkering with QGIS, and signed up for a slew of public/private satellite imagery APIs to bring in data to play with. The EU’s space agency has a lot of really good data sources with fully open access (no user accounts necessary). I am looking forward to working with this new collection of ML-specific tools.
> really good data sources with fully open access (no user accounts necessary) Ola! I am the author of the repo, worked in satellite projects for the Galician goverment some years ago. You don't need an account to download the data from OSM (you do need to contribute back, which makes sense IMO). You don't need an account to download tiles from some publicly available sources (i.e. https://pnoa.ign.es/ in Spain) but…
Thanks so much for the add'l context, that all sounds very real. I have worked in/around academic projects, and maintaining otherwise useful assets and data that follow on from individual projects sounds like a somewhat ubiquitous challenge. I am a systems admin and IT consultant by day, my interests in ML and cartographic endeavors are extra-curricular, but I appreciate what you're doing!