Closed absudabsu closed 6 years ago
I tried with a large batch of images, which are guaranteed to overlap. No luck, same error.
Looking at it again... Perhaps rather np.mean() returning NaN (a warning), the real error is: ERROR 1: No input dataset specified.
? I'm not sure how what I'm doing wrong.. Any hints?
Hello @sirgogo, Thank you for bringing up the problem to our attention. Please, can you send your dataset? Thanks in advance
@dyoussef Thanks for the reply. The dataset I am using is available here: http://www.jhuapl.edu/satellite-benchmark.html . From my understanding, its the same dataset used in the IARPA top coder challenge, but I could be wrong. The specific images I am using are the ones available in the (above, specified) dataset, such as: iarpa_3D-satellite-dataset/Challenge_Data_and_Software/cropimagedata/Explorer/...
I did some more digging, and I think that maybe the issue is due to images not overlapping 100%, since I found that for some image pairs (just two at a time), the algorithm does run, but tries to overallocate memory (I see all kinds of malloc calls on the screen) when it is computing the global DSM. However, for other image pairs, it fails arbitrarily like above.
I tried a similar strategy on a smaller reconstruction are by setting 'full_img' = True
and specifying a small ROI. For some image chips the reconstruction was able to complete (albeit on a very small area)! For other chips, it fails arbitrarily like above.
I have not inspected thoroughly, but from my initial experiments, it seems like the algorithm works/runs when two supplied images are very close (e.g. consecutive), such that their projections cover the same/similar geodesic bounding box with very high overlap, and their image-plane coordinates are also simliar.
Hi sirgogo, Could you please specify the filenames of the input images and provide your full json configuration file so that we can try to reproduce the failure?
From your output I see that the size of your input images is about 2000 x 2000 pixels (from 286 * 7). The original images of the IARPA challenge are much bigger. Maybe your issue comes from the fact that you've cropped the input images without modifying the corresponding RPC coefficients. There's a tool for that: rpc_cropper.
Hi,
I am attempting to run s2p, but I am getting some runtime errors, and I am not sure how to proceed. This is what I've done: I acquired/assembled the XML and TIF files, and edited the config JSON with this information. There are only a few parameters I changed from the basic example that ships with the code: (testdata/input_pair/config.json).
With this assumptions, I tried calling the s2p algorithm. It works great for the input_pair and input_triplet data, but when I run it on my own data (using 3-images from a dataset), I get the following runtime error:
My JSON config_template looks like this:
Any ideas? I was thinking that maybe the images don't cover the same area... which may cause the algorithm to be missing information for some locations. I'm not sure how to get around this, since it seems the utm_bbx was not even used, and it will be hard to tell before-hand whether or not two images contain information that s2p can exploit. Is my interpretation of the error correct? If yes: should it work if I call it with two "overlapping" images?
Thanks in advance!