In [1]:

    

import pandas as pd
import numpy as np
import glob, os
from utils import *
from augment import *
import seaborn as sns
import matplotlib.pyplot as plt
import cPickle

sns.set_style("whitegrid")

%matplotlib inline

label_numbers =  {"Button":0, "Icon":1, "Image":2, "Input field":3, "Line":4, "Text":5, "Navigation Menu":6}
number_label = {0:"Button", 1:"Icon", 2:"Image", 3:"Input field", 4:"Line", 5:"Text", 6: "Navigation Menu"}


    

In [2]:

    

#df = read_txts_and_combine() #uncomment if you want to reread all .txt logs into one .csv
df = pd.read_csv("img_labeled/logs/log_all.csv")
df.head()


    

    
Out[2]:






  

    

      

      
id
      
x_abs
      
y_abs
      
x_rel
      
y_rel
      
width
      
height
      
label
      
filename
    
  
  

    

      
0
      
0
      
233
      
517
      
0.21181818181818182
      
0.7230769230769231
      
94
      
41
      
Image
      
04
    
    

      
1
      
1
      
359
      
522
      
0.32636363636363636
      
0.73006993006993
      
362
      
32
      
Navigation Menu
      
04
    
    

      
2
      
2
      
748
      
520
      
0.68
      
0.7272727272727273
      
23
      
31
      
Icon
      
04
    
    

      
3
      
3
      
776
      
524
      
0.7054545454545454
      
0.7328671328671329
      
15
      
26
      
Icon
      
04
    
    

      
4
      
4
      
796
      
525
      
0.7236363636363636
      
0.7342657342657343
      
18
      
25
      
Icon
      
04
    
  

In [3]:

    

print "Number of labeled webpages: %i"%(len(df.groupby("filename")))
print "Number of labels: %i"%(len(df))


    

    




Number of labeled webpages: 103
Number of labels: 1809

In [4]:

    

print "Number of labels per category:"
print df.groupby("label").count().id


    

    




Number of labels per category:
label
Button             190
Form                70
Icon               273
Image              259
Input field        164
Line               111
List                95
Navigation Menu    119
Rating bar           1
Slider              12
Text               465
Video               18
label               32
Name: id, dtype: int64

In [5]:

    

df.groupby("label").count().id.plot(kind="bar")#, color=sns.color_palette()[0])


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0xbf73198>






    

In [6]:

    

#only take the labels for which we have at least 100 entries
df = filter_top_100(df)
print("%i labels left"%len(df))


    

    




1581 labels left






    




C:\Users\feita1\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\core\indexing.py:549: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  self.obj[item_labels[indexer[info_axis]]] = value

In [7]:

    

#pickle_images("img_labeled/logs/", df)


    

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