In [1]:

    

import numpy as np
from matplotlib import pyplot as plt
import os
import cv2
%matplotlib inline


    

In [2]:

    

trainLoc = '../data/train/'
data = [os.path.join(trainLoc,f) for f in os.listdir(trainLoc)]


    

In [3]:

    

def viewImage(x):
    plt.figure()
    plt.imshow(plt.imread(x))

def getFileLabel(x):
    return x.split(os.path.sep)[-1].split(".")[0]


    

In [4]:

    

viewImage(data[0])
viewImage(data[50])
viewImage(data[120])


    

In [5]:

    

def imageToFeatures(x,size=(32,32)):
    x=cv2.cvtColor(x,cv2.COLOR_RGB2GRAY)
    return cv2.resize(x,size).flatten()


    

In [6]:

    

inputX = np.array([imageToFeatures(cv2.imread(x)) for x in data])
inputY = np.array([getFileLabel(x) for x in data])


    

In [7]:

    

testLoc = '../data/test1/'
testData = [os.path.join(testLoc,f) for f in os.listdir(testLoc)]

testX = np.array([imageToFeatures(cv2.imread(x)) for x in testData])


    

In [21]:

    

import csv
with open('train_data.csv','w') as csvFile:
    writer = csv.writer(csvFile)
    for value in inputX:
        writer.writerow(value)

with open('train_label.csv','w') as csvFile:
    writer = csv.writer(csvFile)
    for value in inputY:
        writer.writerow([value])

with open('test.csv','w') as csvFile:
    writer = csv.writer(csvFile)
    for value in testX:
        writer.writerow(value)


    

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