Preprocessing train dataset

Divide the train folder into two folders mytrain_ox and myvalid_ox



In [2]:

    
from sklearn.model_selection import train_test_split
import seaborn as sns
import os
import shutil
import pandas as pd
%matplotlib inline



In [9]:

    
df = pd.read_csv('list.txt', sep=' ')
df.ix[2000:2005]









    Out[9]:






  
    
      
      IMAGE
      ID
      SPECIES
      BREED
    
  
  
    
      2000
      basset_hound_14
      4
      2
      3
    
    
      2001
      basset_hound_150
      4
      2
      3
    
    
      2002
      basset_hound_151
      4
      2
      3
    
    
      2003
      basset_hound_152
      4
      2
      3
    
    
      2004
      basset_hound_153
      4
      2
      3
    
    
      2005
      basset_hound_154
      4
      2
      3

Visualize the size of the original train dataset.



In [10]:

    
train_cat = df[df['SPECIES'] == 1]
train_dog = df[df['SPECIES'] == 2]
x = ['cat', 'dog']
y = [len(train_cat), len(train_dog)]
ax = sns.barplot(x=x, y=y)

Shuffle and split the train filenames



In [11]:

    
mytrain, myvalid = train_test_split(df, test_size=0.1)
print len(mytrain), len(myvalid)

Visualize the size of the processed train dataset



In [12]:

    
mytrain_cat = mytrain[mytrain['SPECIES'] == 1]
mytrain_dog = mytrain[mytrain['SPECIES'] == 2]
myvalid_cat = myvalid[myvalid['SPECIES'] == 1]
myvalid_dog = myvalid[myvalid['SPECIES'] == 2]
x = ['mytrain_cat', 'mytrain_dog', 'myvalid_cat', 'myvalid_dog']
y = [len(mytrain_cat), len(mytrain_dog), len(myvalid_cat), len(myvalid_dog)]

ax = sns.barplot(x=x, y=y)

Create symbolic link of images



In [16]:

    
def remove_and_create_class(dirname):
    if os.path.exists(dirname):
        shutil.rmtree(dirname)
    os.mkdir(dirname)
    os.mkdir(dirname+'/cat')
    os.mkdir(dirname+'/dog')

remove_and_create_class('mytrain_ox')
remove_and_create_class('myvalid_ox')

for filename in mytrain_cat['IMAGE']:
    os.symlink('../../images/'+filename+'.jpg', 'mytrain_ox/cat/'+filename+'.jpg')

for filename in mytrain_dog['IMAGE']:
    os.symlink('../../images/'+filename+'.jpg', 'mytrain_ox/dog/'+filename+'.jpg')

for filename in myvalid_cat['IMAGE']:
    os.symlink('../../images/'+filename+'.jpg', 'myvalid_ox/cat/'+filename+'.jpg')

for filename in myvalid_dog['IMAGE']:
    os.symlink('../../images/'+filename+'.jpg', 'myvalid_ox/dog/'+filename+'.jpg')



In [ ]:

	IMAGE	ID	SPECIES	BREED
2000	basset_hound_14	4	2	3
2001	basset_hound_150	4	2	3
2002	basset_hound_151	4	2	3
2003	basset_hound_152	4	2	3
2004	basset_hound_153	4	2	3
2005	basset_hound_154	4	2	3