Trimap hangs forever
Rodolphe2005 opened this issue · 3 comments
Rodolphe2005 commented
The following code makes Trimap hang forever.
import numpy as np
import trimap
x = np.array([[ 3.18987876e-01, 5.87170608e-02, -5.35221584e-02,
-2.12370202e-01, 1.44289479e-01, 1.15213081e-01,
-3.49550992e-01, -8.56188014e-02, 7.67039582e-02,
-7.87917897e-02, -2.89615601e-01, -2.38374388e-03,
-6.07468300e-02, -1.53473644e-02, 9.19963419e-02,
-1.14370733e-01, 1.21543720e-01, 1.16481416e-01,
-2.94296652e-01, -1.43486544e-01, -3.29958886e-01,
1.34309351e-01, -4.32708934e-02, 3.27159733e-01,
1.35406721e-04, 2.15839192e-01, -2.31008962e-01,
-1.53630883e-01, 1.70035616e-01, -1.03398576e-01,
-7.83967040e-03, -1.48111418e-01, 7.08103701e-02,
1.51507165e-02, -4.70302580e-03],
[ 2.70511746e-01, 2.50944565e-03, -1.01266943e-01,
-6.04593521e-03, 1.90846086e-01, -5.88433584e-03,
-3.05718035e-01, -1.63746793e-02, 8.91139284e-02,
-3.90956774e-02, -2.89017886e-01, 5.44876307e-02,
-3.34294289e-02, 5.05351350e-02, 1.19450457e-01,
-2.66644936e-02, 1.38987005e-01, 2.54748076e-01,
-2.78318554e-01, 5.58482762e-03, -4.44619954e-01,
-3.14005986e-02, -2.54096221e-02, 3.29968154e-01,
4.54740152e-02, 1.45967603e-01, -1.36808544e-01,
-1.10377215e-01, 1.64085761e-01, -2.38455474e-01,
-1.35548353e-01, -1.64852977e-01, 1.17668778e-01,
-4.60316762e-02, 4.73128930e-02],
[ 3.17780316e-01, -7.81738758e-03, -6.44788519e-02,
5.62540069e-02, 1.69442132e-01, 5.34028653e-03,
-3.56567532e-01, 9.72701795e-03, 8.40950683e-02,
-7.36852437e-02, -3.20505381e-01, 2.87447236e-02,
-8.96242410e-02, 1.10711388e-01, 3.08006257e-02,
-1.42246597e-02, 7.26564825e-02, 3.26128125e-01,
-1.96420610e-01, -8.66924319e-03, -3.05779576e-01,
-2.30795946e-02, 9.55938771e-02, 3.96909148e-01,
7.82142058e-02, 1.47577658e-01, -9.03981999e-02,
-4.88963164e-02, 1.18389614e-01, -2.15027452e-01,
-6.54470399e-02, -1.75441504e-01, 1.87194660e-01,
-5.08111436e-04, 1.35444716e-01],
[ 2.58012921e-01, -8.77735093e-02, -1.28023893e-01,
1.47463515e-01, 2.61107385e-01, -5.92785887e-02,
-2.14058936e-01, 3.41764428e-02, 4.58676219e-02,
-4.56911102e-02, -2.89655060e-01, -1.57761140e-04,
-4.51611951e-02, 7.53968805e-02, 7.84260333e-02,
5.99992424e-02, 1.10423878e-01, 3.26432049e-01,
-2.62022614e-01, 2.30244398e-02, -3.76471043e-01,
-1.13793373e-01, 1.96540896e-02, 2.30564684e-01,
6.99499100e-02, 1.44859001e-01, 5.51677980e-02,
2.79185660e-02, 7.44636357e-02, -2.78124183e-01,
-1.65953085e-01, -1.10599346e-01, 2.63543546e-01,
-8.91586766e-02, 1.93403229e-01],
[ 3.32011819e-01, -1.40174493e-01, -5.28167412e-02,
1.13800459e-01, 2.06157431e-01, -8.29892382e-02,
-2.11161330e-01, 7.94143155e-02, 4.90802489e-02,
-1.19306277e-02, -2.87060529e-01, 4.33459552e-03,
8.65805820e-02, 3.03589255e-02, 1.73449665e-01,
1.71231180e-02, 4.74411622e-02, 2.65454501e-01,
-2.75403082e-01, 2.34591905e-02, -3.79175991e-01,
-1.03660703e-01, 4.20364253e-02, 1.28694892e-01,
-8.52392241e-03, -4.99439947e-02, 1.10806182e-01,
-2.32070358e-03, 2.65163928e-02, -3.77998233e-01,
-2.85796434e-01, -7.88480118e-02, 1.74133658e-01,
-1.40881404e-01, 1.08900480e-01],
[ 1.82337701e-01, -2.11179242e-01, -1.01714216e-01,
1.31016269e-01, 4.99383882e-02, -1.59250170e-01,
-1.29212305e-01, -3.32643799e-02, 1.20454393e-01,
1.02800533e-01, -2.92455345e-01, -1.76530272e-01,
2.09684089e-01, 1.33223221e-01, 1.39211901e-02,
4.81586717e-03, -9.83966216e-02, 3.23559731e-01,
-2.28622139e-01, 3.68424207e-02, -2.63355613e-01,
-1.88473210e-01, 4.12943624e-02, 1.66466340e-01,
-1.77660301e-01, -1.06210433e-01, 2.31963158e-01,
-5.21184653e-02, 8.36717412e-02, -2.57204562e-01,
-2.26933807e-01, -1.83641464e-01, 2.42122248e-01,
-1.56716019e-01, 4.54310402e-02],
[ 2.46496126e-02, -1.26516521e-01, -2.60583401e-01,
2.04805687e-01, 1.16600819e-01, -2.23044977e-01,
-1.97046809e-02, -8.16227198e-02, 7.48965740e-02,
1.76039010e-01, -2.80806333e-01, -9.68108177e-02,
1.12287454e-01, 1.50147453e-01, -7.96348378e-02,
4.77459133e-02, 3.08816843e-02, 2.76006699e-01,
-2.06872299e-01, 1.46334590e-02, -2.49763101e-01,
-1.79324538e-01, -2.08251923e-02, 1.89528510e-01,
-9.29871425e-02, 1.07009195e-01, 2.11045280e-01,
-3.39877009e-02, 7.40684122e-02, -1.97052538e-01,
-8.61336514e-02, -2.74793237e-01, 3.87020469e-01,
-7.57661313e-02, 1.86928004e-01]], dtype=np.float32)
y = trimap.TRIMAP(verbose=True).fit_transform(x)
eamid commented
Hi Rodolphe,
Thanks for noticing this. Both parameters n_inliers and n_outliers should be < n-1. Since the shape of your input is (7, 37), you should try (n_inliers < 6, n_outliers < 6). I tried:
y = trimap.TRIMAP(n_inliers=5, n_outliers=5).fit_transform(x)
and it worked fine. I will add conditions to check for such cases.
Rodolphe2005 commented
thank you !
Le mer. 23 oct. 2019 à 20:18, Ehsan Amid <notifications@github.com> a
écrit :
… Hi Rodolphe,
Thanks for noticing this. Both parameters n_inliers and n_outliers should
be < n-1. Since the shape of your input is (7, 37), you should try
(n_inliers < 6, n_outliers < 6). I tried:
y = trimap.TRIMAP(n_inliers=5, n_outliers=5).fit_transform(x)
and it worked fine. I will add conditions to check for such cases.
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eamid commented
Hi @Rodolphe2005,
I fixed the issue. It should work fine now. Thank you again for letting me know about the bug!