build_confusion_array.py
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00001 import os, sys
00002 from numpy import *
00003 import matplotlib.pyplot as plt
00004 from pylab import *
00005 
00006 conf_array_array = []
00007 
00008 def buildConfusionMatrix(path,nr):
00009     for i in range(1, int(nr)):
00010         input = open(path)
00011         #print "range: ", i
00012         k = l = 0
00013         nr_lines = 0
00014         conf_array = []
00015         for el in range(1, int((nr))):
00016             conf_array.append(0)
00017         for line in input.xreadlines():
00018             #print "line: ", line.split()
00019 #            j = [int(line.split()[0])/10, int(line.split()[1])/10]
00020             j = [int(line.split()[0]), int(line.split()[1])]
00021             if i == int(j[1]):
00022                conf_array[int(j[0]) - 1] =  conf_array[int(j[0]) - 1] + 1
00023             #nr of lines
00024             nr_lines = nr_lines + 1
00025         print "nr lines", nr_lines
00026         #print conf_array
00027         conf_array_array.append(conf_array)
00028         input.close()
00029     print 'rows are ground truth, columns the classification: ', conf_array_array
00030     compute_false_pos_statistics(conf_array_array)
00031     plot_confusion_matrix(conf_array_array, int(nr)-1)
00032 
00033 def plot_confusion_matrix(conf_arr, nr):
00034     norm_conf = []
00035     for i in conf_arr:
00036         a = 0
00037         tmp_arr = []
00038         a = sum(i,0)
00039         for j in i:
00040                 if j == 0 and a == 0:
00041                         tmp_arr.append(0)
00042                 else:
00043                         tmp_arr.append(float(j)/float(a))
00044                 #tmp_arr.append(j)
00045         norm_conf.append(tmp_arr)
00046 
00047     plt.clf()
00048     fig = plt.figure()
00049 #    plt.xticks( arange(nr), ('SmallCylinder',  'FlatBigBox',  'TetraPak',  'MediumBox',  'Teapot',  'TallCylinder'), rotation=90)
00050 #    plt.yticks( arange(nr), ('SmallCylinder',  'FlatBigBox',  'TetraPak',  'MediumBox',  'Teapot',  'TallCylinder') )
00051     plt.xticks( arange(nr), ('bowl',  'box_medium',  'box_small',  'cylinder_big',  'cylinder_short',  'cylinder_small', 'flat_big', 'flat_small', 'pan', 'plate', 'tetrapak'), rotation=90)
00052     plt.yticks( arange(nr), ('bowl',  'box_medium',  'box_small',  'cylinder_big',  'cylinder_short',  'cylinder_small', 'flat_big', 'flat_small', 'pan', 'plate', 'tetrapak') )
00053 #    plt.title('GRSD Confusion Matrix for Training Views')
00054     plt.title('GRSD Confusion Matrix for Training Objects')
00055     ax = fig.add_subplot(111)
00056     res = ax.imshow(array(norm_conf),  cmap=cm.jet, interpolation='nearest', aspect='auto')
00057     cb = fig.colorbar(res)
00058     savefig("confmat.png", format="png", bbox_inches='tight')
00059 
00060 def compute_false_pos_statistics(conf_arr):
00061     tp = 0
00062     all = 0
00063     array_len = conf_arr.__len__()
00064     for i in range(array_len):
00065         tp = tp + conf_arr[i][i]
00066         all = all + sum(conf_arr[i])
00067     print 'all: ', all, 'true positives: ', tp, 'percentage: ', double(tp)/double(all)
00068 
00069 
00070 if __name__ == "__main__":
00071     if sys.argv.__len__() < 3:
00072         print "Usage: build_confusion_matrix.py \t test.conf \t number_of_classes+1 \n\nAlso, adopt lines plt.xticks plt.yticks with actual category names"
00073         sys.exit()
00074     path = sys.argv[1]
00075     nr = sys.argv[2]
00076     buildConfusionMatrix(path, nr)
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pcl_cloud_tools
Author(s): Nico Blodow, Zoltan-Csaba Marton, Dejan Pangercic
autogenerated on Thu May 23 2013 17:11:35