This file is indexed.

/usr/share/pyshared/gamera/classifier_stats.py is in python-gamera 3.3.2-2.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
# -*- mode: python; indent-tabs-mode: nil; tab-width: 3 -*-
# vim: set tabstop=3 shiftwidth=3 expandtab:
#
# Copyright (C) 2001-2005 Ichiro Fujinaga, Michael Droettboom,
#                          and Karl MacMillan
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#

import os, os.path
from gamera import util
from gamera.core import *

class ClassifierStat:
   def __init__(self, classifier, path, max_size=64):
      self.classifier = classifier
      self.path = path
      if not os.path.exists(path):
         os.makedirs(path)
      self.image_path = os.path.join(path, "images")
      if not os.path.exists(self.image_path):
         os.makedirs(self.image_path)
      self.max_size = max_size

   def make_example_glyphs(self):
      self.example_glyphs = {}
      for glyph in self.classifier.get_glyphs():
         for conf, id in glyph.id_name:
            if not self.example_glyphs.has_key(id):
               self.example_glyphs[id] = glyph

   def make_grid(self, rows, cols):
      grid = []
      for i in range(rows):
         row = [None] * cols
         grid.append(row)
      return grid

   def make_pages(self):
      grids = self.make_result()
      for name, grid in grids:
         filename = os.path.join(self.path, name.lower().replace(" ", "_"))
         self.make_html(filename + ".html", name, grid)
         self.make_csv(filename + ".csv", name, grid)

   def make_html(self, filename, name, grid):
      fd = open(filename, "w")
      fd.write("<html><head><title>%s</title></head><body><h1>%s</h1>" %
               (name, name))
      fd.write("<table>")
      for row in grid:
         fd.write("<tr>")
         for col in row:
            fd.write("<td>")
            if isinstance(col, ImageBase):
               id = col.get_main_id()
               image_filename = "images/%s.png" % id
               col.save_PNG(os.path.join(self.path, image_filename))
               fd.write('<img src="%s" width="%d" height="%d"/><br/>%s' %
                        (image_filename, min(col.width, self.max_size),
                         min(col.height, self.max_size), id))
            elif col is None:
               fd.write("&nbsp;")
            else:
               fd.write(str(col))
            fd.write("</td>")
         fd.write("</tr>")
      fd.write("</table>")
      fd.write("</body></html>")
      fd.close()

   def make_csv(self, filename, name, grid):
      def convert(x):
         if isinstance(x, ImageBase):
            return x.get_main_id()
         elif x == None:
            return ""
         else:
            return str(x)
      fd = open(filename, "w")
      for row in grid:
         formatted_row = ", ".join([convert(x) for x in row])
         fd.write(formatted_row)
         fd.write("\n")
      fd.close()
            
class ConfusionMatrix(ClassifierStat):
   title = "Confusion Matrix"
   
   def make_result(self):
      self.make_example_glyphs()
      result = {}
      for id0 in self.example_glyphs.keys():
         leaf = {}
         for id1 in self.example_glyphs.keys():
            leaf[id1] = 0
         result[id0] = leaf
         
      classifier = self.classifier
      glyphs = classifier.get_glyphs()
      progress = util.ProgressFactory("Generating confusion matrix...", len(glyphs) / 50)
      try:
         for i, glyph in enumerate(glyphs):
            guess = classifier.classify_with_images(glyphs, glyph, True)
            result[glyph.get_main_id()][guess[0][1]] += 1
            if i % 50 == 0:
               progress.step()
      finally:
         progress.kill()

      ids = result.keys()
      ids.sort()
      grid = self.make_grid(len(ids) + 1, len(ids) + 1)
      for i, id in enumerate(ids):
         grid[0][i+1] = self.example_glyphs[id]
         grid[i+1][0] = self.example_glyphs[id]
      for i, id0 in enumerate(ids):
         res = result[id0]
         sum = 0
         for val in res.values():
            sum += val
         for j, id0 in enumerate(ids):
            grid[i+1][j+1] = str(int((float(res[id0]) / sum) * 100.0)) + "%"
      return [("Confusion Matrix", grid)]

class ClassNameHistogram(ClassifierStat):
   title = "Class Name Histogram"

   def make_result(self):
      self.make_example_glyphs()
      result = {}
      for id0 in self.example_glyphs.keys():
         result[id0] = 0

      for glyph in self.classifier.get_glyphs():
         id = glyph.get_main_id()
         result[id] += 1

      result = [(val, key) for key, val in result.items()]
      result.sort()
      result.reverse()

      grid = self.make_grid(len(self.classifier.get_glyphs()), 2)
      for i, (val, key) in enumerate(result):
         grid[i][0] = self.example_glyphs[key]
         grid[i][1] = val
      return [("Class Name Histogram", grid)]

all_stat_pages = [ConfusionMatrix, ClassNameHistogram]
def make_stat_pages(classifier, path, pages=None, max_size=64):
   if pages is None:
      pages = all_stat_pages
   for page in pages:
      name = page.__name__.lower()
      page_path = os.path.join(path, name)
      p = page(classifier, page_path, max_size)
      p.make_pages()