notebook.community

Edit and run



In [1]:

    
%pylab
%matplotlib inline









    



Using matplotlib backend: agg
Populating the interactive namespace from numpy and matplotlib



In [2]:

    
cd ..









    



/home/scott/Documents/git/neukrill-net-work



In [3]:

    
import sys
import numpy as np
import skimage
import cv2
import sklearn
import imp



In [4]:

    
from holoviews import *









    



:0: FutureWarning: IPython widgets are experimental and may change in the future.



In [5]:

    
import neukrill_net.utils
import neukrill_net.highlevelfeatures



In [6]:

    
settings = neukrill_net.utils.Settings('settings.json')



In [7]:

    
X,y = settings.flattened_train_paths(settings.classes)



In [8]:

    
attrlst = ['height','width','numpixels','aspectratio','mean','std','stderr','numwhite','propwhite','numnonwhite','propnonwhite','numblack','propblack','numbool','propbool']

Checking what the smallest image sizes are



In [9]:

    
hlf = neukrill_net.highlevelfeatures.BasicAttributes(['height','width'])



In [10]:

    
XA = hlf.transform(X)



In [11]:

    
XA.shape









    Out[11]:





(1, 30336, 2)



In [12]:

    
np.amin(XA,1)









    Out[12]:





array([[ 21.,  31.]])



In [13]:

    
XA_ = hlf.transform(settings.image_fnames['test'])



In [14]:

    
XA_.shape









    Out[14]:





(1, 130400, 2)



In [15]:

    
np.amin(XA_,1)









    Out[15]:





array([[ 21.,  31.]])

Use all the attributes



In [ ]:

    
hlf = neukrill_net.highlevelfeatures.BasicAttributes(attrlst)