4 ms·
As with all these "this X doesn't exist" sites, the images look ok at first sight, but when you start to look closer you notice that some things aren't quite ri
by rob74 5y ago
As with all these "this X doesn't exist" sites, the images look ok at first sight, but when you start to look closer you notice that some things aren't quite right. In this case, it's mostly roads that don't seem to connect to anything...
- ogig 5y agoAs someone spending time looking at satellite and orthographic photos, i agree, this looks weird. City grid looks like cloth texture, roads and rivers make no sense. In any case, it manages to slightly impress me.
- sdflhasjd 5y agoIt's like it can't decide between a city on a grid or not, and instead ends up with a weird fusion of both - and like you said - looks like a woven fabric instead.
- dTal 5y ago>As someone spending time looking at satellite and orthographic photos That's presumably the same training the AI had :p
- warmwaffles 5y agoHow does one get an orthographic photo that is not artificially made? I know what an orthographic camera does in 3D graphics, but how can you accomplish that in a real life?
- detaro 5y agothey are "artificially made" by postprocessing aerial images. (You can actually do cameras that create orthographic images, but that's more for industrial vision etc since the frame covered obviously can't be larger than the lens, which doesn't really work for aerial photography, so if people talk about "ortophotos" in that sense they mean processed)
- hajhatten 5y agoI'm surprised you managed to notice that. The images are so low res.
- notahacker 5y agoYep. I was quite impressed by how mine appeared to stick bridges in logical positions. Then I noticed one of them only got halfway across the river...
- brk 5y agoThat's not a bug, it's just bureaucracy. Wait 6 months and refresh.
- msdrigg 5y agoI wonder if you could improve this GAN by taking a cropped part of each generated image and trying to discriminate against that part of the image as well. Because the problem seems to be in the details. The GAN is great at the global picture but the details are off. And this problem benefits from the fact that a picture of a section of a city should also be recognized as a picture of a city.