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View Code? Open in Web Editor NEWConvolutional neural network code for extracting Lunar craters from Digital Elevation Maps (DEMs).
License: MIT License
Convolutional neural network code for extracting Lunar craters from Digital Elevation Maps (DEMs).
License: MIT License
Could you tell me how to use "USGS Astrogeology Cloud Processing service"? Thank you very much for your kind consideration and I am looking forward to your early reply.
The way you are cropping the images randomly to generate the datasets. Does it generates data leakage? Thanks
The loss often reaches "Nan" when I run the run_model_train, but I haven't found a solution yet. Have you ever run into this situation?
@cczhu since you changed get_unique_craters.py there is now a bug in there somewhere. I ran a new set of extracting crater distributions and there are tons of nan entries in the long/lat coordinates, e.g.
[ nan nan 4.65171524]
[ nan nan 3.4377277]
[ nan nan 7.02831142]
[ nan nan 3.58227701]
not sure yet at the moment where the problem is, but you might better understand where it could be coming from? My guess is that it has to do with taking np.sin
or np.cos
of a number not in [-1,1] range, but I actually don't know at the moment. If you don't think you have time to look into this then I will.
It might ultimately be easier for me to look at it since I have the get_unique_craters.py pipeline set up and could just print everything every time a nan shows up....
Charles - Py 2.7/3.5
Ari - Keras & TF
Can you provide Mercury DEM images?Thanks
I think that the train/dev/test datasets belong on zenodo (and provide a shareable link in the DeepMoon readme and paper), but I think a final CNN-predicted crater distribution (for train/dev/test) belongs in this repo (in csv format), in the same folder as our LROC and Head datasets. What do you think @cczhu?
Hi, I just found there are some difference between the equation and the code in the function estimate_longlatdiamkm from get_unique_craters.py. That is , how to convert the pixel coordinate into latitude/longitude coordinate. Specifically, why there is sin and cos here.
lat_deg = lat_central - (deg_per_pix * (lat_pix - dim[1] / 2.) *
(np.pi * latdiff / 180.) /
np.sin(np.pi * latdiff / 180.))
# Determine longitude using determined latitude.
long_deg = long_central + (deg_per_pix * (long_pix - dim[0] / 2.) /
np.cos(np.pi * lat_deg / 180.))
I ran pytest test_get_unique_craters.py
in my Python 2 and Python 3 virtualenvs, and in the Python 3 one it template_match_t2c
returned N_match == 0
under the test_extract
test. Not obvious why this is happening on a quick inspection of the function.
Chase Roberts created mltest for some simple tests of convnet integrity self-consistency. His code works for TensorFlow, and we support a version of Keras that can't auto-convert to TF, so perhaps we can rewrite his test suite for Keras use.
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