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by daavoo
446 days ago
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Hi, sorry if the project or narrative gave the wrong impression but my idea was to show the potential, not providing a polished solution. As disclaimed in the demo and code, the example model was trained only with data from Galicia on a Google Colab. A robust enough models would require more data and compute. > it's definitely uploading crap. What was uploaded was what a human approved. > It's useful for finding ones that haven't been mapped but not for drawing them. It can get the 4 corners pretty accurate for pools that are square, many are half round at the ends though I couldn't dedicate enough time on the best way to refine the predictions, but happy to hear and discuss any ideas. Ideas I have are: - Try an oriented bounding box model instead of detection + segmentation. It will not be useful for not square shapes but will definitely generate more accurate predictions.
- Build some sort of https://es.wikipedia.org/wiki/RANSAC that tries to fits rectangles and/or other shapes as an step to postprocess the predicted mask. |
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Yes, I hit approve on the best one because I was curious to see the actual final polygon. (I then went and fixed it.) You wrote above / I was responding to:
>> This is a because the polygon is drawn as a mask in order to overlay it on the image. The actual polygon being uploaded doesn't have the wobbly features.
Now you're saying it's my fault for selecting a wonky outline. What's it gonna be, is the preview bad or the resulting polygons? (And the reviewer is bad for approving anything at all?)
> my idea was to show the potential, not providing a polished solution
I can appreciate that, but if you're aware of this then it shouldn't have a button that unauthenticated users can press to upload the result to the production database. OSM has testing infrastructure if you want to also demo that part (https://master.apis.dev.openstreetmap.org/ is a version I found on https://wiki.openstreetmap.org/wiki/API_v0.6)