Python and Matlab bindings for Damascene, Global Probabilty of Boundary on GPU

So I'm still playing around with constrained parametric min-cuts for object segmentation. A major bottleneck of this algorithm is gPb, the global probability of boundary operator from Malik's group.
Luckily, there already is a CUDA implementation of gPb out there: Damascene.
Damascene provides a command line interface to apply gPb to ppm images.
Since I wanted to include it directly with cpmc, I wrote some mex-wrappers for Damascene. And since I would love to see more algorithms done in Python instead of Matlab, I wrote some Python wrappers, too.
You can find both, together with the current version of damascene here.
You need a working CUDA setup and the acm library to compile it.
Set your paths in common.mk and just "make" it.
For the matlab wrappers, you also need to adjust the matlab path in "bindings/Makefile" and "make gpb_mex" in that directory.
For the python wrappers, you have to compile damascene with "make shared=1". Then you can simply call gpu_gpb.py inside the bindings directory.

If you only have the students' version of Matlab, like me, you can use the file "common_32.mk" instead of common.mk to cross-compile damascene. You will probably have to adjust some paths in there, too.

I'd like to thank Bryan Catanzaro for making Damascene public. It's really a great tool!

Comments

  1. Hi,
    Thanks a lot for the useful work and sharing it with the community
    Before going to matlab wrappers, i just wanted to run damascene in C++. After successful compilation, I've got this runtime error:
    "Assertion failed: screenedEigVals.size() >= p_nEigNum"
    Do you happen having faced this error?
    Could you help me solve this problem?
    Thanks in advance
    Best regards

    ReplyDelete
  2. Hi.
    Nope, I never ran into this problem. What command line arguments did you use? Did you try the default parameters?
    Cheers,
    Andy

    ReplyDelete
  3. I did not find any default parameters nor a sample ppm image. I just used some images of mine and played with the parameters values but still having the same error.
    Could you please send me an image and corresponding parameters that work
    Thanks

    ReplyDelete
  4. There is a file called "polynesia.ppm" in the "damascene" subfolder.
    Just call damascene with this file and no other arguments
    like this (my damascene executable is in some release folder at that point)
    "./damascene ../../../damascene/polynesia.ppm "

    ReplyDelete
  5. Thanks for the hint. But this is what i've got

    Using cuda device 0: Quadro FX 3800
    Processing: polynesia.ppm, output in polynesiaPb.pgm and polynesia.pb

    Eig 9 Tol 0.001000 Texton 1Image found: 321 x 481 pixels
    Available 874888704 bytes on GPU
    >+< rgbUtoGrayF | 0.088000 | ms
    Convolving
    Beginning kmeans
    Changes: 150510
    Changes: 75038
    Changes: 49962
    Changes: 36991
    Changes: 30317
    Changes: 24616
    Changes: 20667
    Changes: 17589
    Changes: 15044
    Changes: 12782
    Changes: 10673
    Changes: 8873
    Changes: 7254
    Changes: 5789
    Changes: 4663
    15 iterations until termination
    Kmeans completed
    >+< texton | 235.102005 | ms
    >+< rgbUtoLab3F | 0.181000 | ms
    >+< normalizeLab | 0.004000 | ms
    >+< mirrorImage | 1.537000 | ms
    Beginning Local cues computation
    >+< Bgsmooth: | 45.691002 | ms
    >+< Bg: | 276.975006 | ms
    >+< Cgsmooth: | 101.719002 | ms
    >+< Cga: | 315.234985 | ms
    >+< Cgsmooth: | 101.391998 | ms
    >+< Cgb: | 317.585999 | ms
    >+< Tgsmooth: | 97.671997 | ms
    >+< Tg: | 254.839996 | ms
    Completed Local cues
    localcues time: 1.198925 seconds
    >+< localcues | 1198.927979 | ms
    >+< combine | 0.374000 | ms

    Max time: 0.000117 seconds
    Oriented Max time: 0.001017 seconds
    Solve time: 0.001145 seconds
    >+< nonmaxsupression | 3.273000 | ms
    Intervening contour completed
    >+< intervene | 37.535000 | ms
    Available 804051968 bytes on GPU
    Can fit 1158 iterations on GPU
    lanczos iteration: 0
    lanczos iteration: 100
    lanczos iteration: 200
    lanczos iteration: 300
    lanczos iteration: 400
    Screened Eigenvalues:
    nan nan 0.000000e+00
    damascene: lanczos.cu:360: void CullumDevice(int, float*, float*, double*, double*, int, float*, float*, int, float*, double*, char, char, double, double, int, int, double, int, double*, int*, int*, double*, int*, int*): Assertion `screenedEigVals.size() >= p_nEigNum' failed.
    Abandon

    ReplyDelete
  6. Weird.
    Seems to be some numerical problem. Which version of damascene are you using? I'm using 0.1.4. Can you try another GPU?
    Maybe try the CUDA memtest tool: http://sourceforge.net/projects/cudagpumemtest/

    ReplyDelete
  7. I used the source files provided by your package (0.1.4) and finally it works! :))
    It's weird that in the damascene page (http://www.cs.berkeley.edu/~catanzar/Damascene/),the version provided is 0.1 and not the 0.1.4.
    I wonder where have you downloaded the 0.1.4 version?
    Thanks a lot anyway for helping me :)

    ReplyDelete
  8. There is another place to download it. Follow the link at "favourite code" at the right.
    I notice they have 0.1.5 now.
    Since you had so much trouble with the older version, maybe you should tell them to update their links.
    Cheers,
    Andy

    ReplyDelete
  9. There was a minor fix in 0.1.5, which I included in my matlab and python bindings. If you want, you can get them here:
    https://github.com/amueller/damascene-python-and-matlab-bindings

    ReplyDelete
  10. I just sent an e-mail to Damascene author

    ReplyDelete

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