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!apt-get install -y unzip
!wget https://pythonprogramming.net/static/downloads/image-recognition/tutorialimages.zip
!unzip tutorialimages.zip
!cp images/numbers/3.8.png images/test.png
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%matplotlib inline
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
import time
def threshold(imageArray):
balanceAr = []
newAr = imageArray
for eachRow in imageArray:
for eachPix in eachRow:
avgNum = reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3])
balanceAr.append(avgNum)
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i = Image.open('images/numbers/0.1.png')
iar = np.array(i)
i2 = Image.open('images/numbers/y0.4.png')
iar2 = np.array(i2)
i3 = Image.open('images/numbers/y0.5.png')
iar3 = np.array(i3)
i4 = Image.open('images/sentdex.png')
iar4 = np.array(i4)
fig = plt.figure()
ax1 = plt.subplot2grid((8,6),(0,0), rowspan=4, colspan=3)
ax2 = plt.subplot2grid((8,6),(4,0), rowspan=4, colspan=3)
ax3 = plt.subplot2grid((8,6),(0,3), rowspan=4, colspan=3)
ax4 = plt.subplot2grid((8,6),(4,3), rowspan=4, colspan=3)
ax1.imshow(iar)
ax2.imshow(iar2)
ax3.imshow(iar3)
ax4.imshow(iar4)
plt.show()
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def threshold(imageArray):
balanceAr = []
newAr = imageArray
for eachRow in imageArray:
for eachPix in eachRow:
avgNum = reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3])
balanceAr.append(avgNum)
balance = reduce(lambda x, y: x + y, balanceAr) / len(balanceAr)
for eachRow in newAr:
for eachPix in eachRow:
if reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3]) > balance:
eachPix[0] = 255
eachPix[1] = 255
eachPix[2] = 255
eachPix[3] = 255
else:
eachPix[0] = 0
eachPix[1] = 0
eachPix[2] = 0
eachPix[3] = 255
return newAr
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i = Image.open('images/numbers/0.1.png')
iar = np.array(i)
i2 = Image.open('images/numbers/y0.4.png')
iar2 = np.array(i2)
i3 = Image.open('images/numbers/y0.5.png')
iar3 = np.array(i3)
i4 = Image.open('images/sentdex.png')
iar4 = np.array(i4)
iar = threshold(iar)
iar2 = threshold(iar2)
iar3 = threshold(iar3)
iar4 = threshold(iar4)
fig = plt.figure()
ax1 = plt.subplot2grid((8,6),(0,0), rowspan=4, colspan=3)
ax2 = plt.subplot2grid((8,6),(4,0), rowspan=4, colspan=3)
ax3 = plt.subplot2grid((8,6),(0,3), rowspan=4, colspan=3)
ax4 = plt.subplot2grid((8,6),(4,3), rowspan=4, colspan=3)
ax1.imshow(iar)
ax2.imshow(iar2)
ax3.imshow(iar3)
ax4.imshow(iar4)
plt.show()
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def createExamples():
numberArrayExamples = open('numArEx.txt','a')
numbersWeHave = range(1,10)
for eachNum in numbersWeHave:
#print eachNum
for furtherNum in numbersWeHave:
# you could also literally add it *.1 and have it create
# an actual float, but, since in the end we are going
# to use it as a string, this way will work.
print(str(eachNum)+'.'+str(furtherNum))
imgFilePath = 'images/numbers/'+str(eachNum)+'.'+str(furtherNum)+'.png'
ei = Image.open(imgFilePath)
eiar = np.array(ei)
eiarl = str(eiar.tolist())
print(eiarl)
lineToWrite = str(eachNum)+'::'+eiarl+'\n'
numberArrayExamples.write(lineToWrite)
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createExamples()
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from PIL import Image
import numpy as np
import time
from collections import Counter
def whatNumIsThis(filePath):
matchedAr = []
loadExamps = open('numArEx.txt','r').read()
loadExamps = loadExamps.split('\n')
i = Image.open(filePath)
iar = np.array(i)
iarl = iar.tolist()
inQuestion = str(iarl)
for eachExample in loadExamps:
try:
splitEx = eachExample.split('::')
currentNum = splitEx[0]
currentAr = splitEx[1]
eachPixEx = currentAr.split('],')
eachPixInQ = inQuestion.split('],')
x = 0
while x < len(eachPixEx):
if eachPixEx[x] == eachPixInQ[x]:
matchedAr.append(int(currentNum))
x+=1
except Exception as e:
print(str(e))
print(matchedAr)
x = Counter(matchedAr)
print(x)
print(x[0])
whatNumIsThis('images/test.png')
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from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
import time
from collections import Counter
from matplotlib import style
style.use("ggplot")
def createExamples():
numberArrayExamples = open('numArEx.txt','a')
numbersWeHave = range(1,10)
for eachNum in numbersWeHave:
for furtherNum in numbersWeHave:
imgFilePath = 'images/numbers/'+str(eachNum)+'.'+str(furtherNum)+'.png'
ei = Image.open(imgFilePath)
eiar = np.array(ei)
eiarl = str(eiar.tolist())
lineToWrite = str(eachNum)+'::'+eiarl+'\n'
numberArrayExamples.write(lineToWrite)
def threshold(imageArray):
balanceAr = []
newAr = imageArray
for eachPart in imageArray:
for theParts in eachPart:
# for the reduce(lambda x, y: x + y, theParts[:3]) / len(theParts[:3])
# in Python 3, just use: from statistics import mean
# then do avgNum = mean(theParts[:3])
avgNum = reduce(lambda x, y: x + y, theParts[:3]) / len(theParts[:3])
balanceAr.append(avgNum)
balance = reduce(lambda x, y: x + y, balanceAr) / len(balanceAr)
for eachRow in newAr:
for eachPix in eachRow:
if reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3]) > balance:
eachPix[0] = 255
eachPix[1] = 255
eachPix[2] = 255
eachPix[3] = 255
else:
eachPix[0] = 0
eachPix[1] = 0
eachPix[2] = 0
eachPix[3] = 255
return newAr
def whatNumIsThis(filePath):
matchedAr = []
loadExamps = open('numArEx.txt','r').read()
loadExamps = loadExamps.split('\n')
i = Image.open(filePath)
iar = np.array(i)
iarl = iar.tolist()
inQuestion = str(iarl)
for eachExample in loadExamps:
try:
splitEx = eachExample.split('::')
currentNum = splitEx[0]
currentAr = splitEx[1]
eachPixEx = currentAr.split('],')
eachPixInQ = inQuestion.split('],')
x = 0
while x < len(eachPixEx):
if eachPixEx[x] == eachPixInQ[x]:
matchedAr.append(int(currentNum))
x+=1
except Exception as e:
print(str(e))
x = Counter(matchedAr)
print(x)
graphX = []
graphY = []
ylimi = 0
for eachThing in x:
graphX.append(eachThing)
graphY.append(x[eachThing])
ylimi = x[eachThing]
fig = plt.figure()
ax1 = plt.subplot2grid((4,4),(0,0), rowspan=1, colspan=4)
ax2 = plt.subplot2grid((4,4),(1,0), rowspan=3,colspan=4)
ax1.imshow(iar)
ax2.bar(graphX,graphY,align='center')
plt.ylim(400)
xloc = plt.MaxNLocator(12)
ax2.xaxis.set_major_locator(xloc)
plt.show()
whatNumIsThis('images/test.png')