def getFeatures(img):
featureList = []
cv2.imshow("Before ", img)
img = normalizer.getNormalizedImage(img)
#cv2.imshow("SEEM ME AFTER nomralization",img)
#cv2.waitKey()
zones = getZonesValue(img)
#fourierT = getFourierTransformvalues(img)
#print(fourierT)
wavelet = waveletTransform(img)
for i in zones:
featureList.append(i)
featureList += crossings(img)
featureList.append(getMoment(img))
# for i in fourierT:
# featureList.append(i)
for i in img:
x = get_bit_reversed_list(i)
for j in x:
featureList.append(j)
for i in wavelet:
featureList.append(i)
return featureList
def getFeatures(img):
featureList=[]
img=normalizer.getNormalizedImage(img)
intersections = getCrossing(img)
for i in intersections :
featureList.append(i)
'''
zones=getZonesValue(img)
for i in zones:
featureList.append(i)
'''
return featureList
def getFeatures(img):
featureList = []
# cv2.imshow("SEEM ME Before nomralization", img)
img = normalizer.getNormalizedImage(img)
# cv2.imshow("SEEM ME AFTER nomralization",img)
# cv2.waitKey()
zones = getZonesValue(img)
for i in zones:
featureList.append(i)
featureList += crossings(img)
featureList += (getMoment(img))
featureList += getEndPointsNIntersectionPoints(img)
# featureList+=getFourierTransformvalues(img).tolist()
return featureList
print(chr(eclf1.predict(Features.getFeatures(croppedImage))[0]),
end=" ")
stri = "Candidates after classification, probability wise ::: \n"
for i in range(0, min(5, len(sortedLetters))):
stri += sortedLetters[i][0] + "(" + str(
round(sortedLetters[i][1], 2)) + ")" + " , "
fig = plt.figure(figsize=(4.6, 4.6))
ax = fig.add_subplot(1, 2, 1)
ax.imshow(cv2.resize(croppedImage, (24, 24)), cmap='gray')
ax.set_title("Segmented character")
# plt.imshow(croppedImage,cmap='gray')
ax = fig.add_subplot(122)
ax.imshow(normalizer.getNormalizedImage(croppedImage), cmap='gray')
ax.set_title("Thinned Image")
plt.suptitle(stri)
plt.show()
print()
'''extractingLines.doit(image)
components=componentGetter.getComponents(image)
print(len(components))
per=[]
pery=[0 for i in range(len(components))]
cenx=[];ceny=[]
for i in components:
per.append(len(i))
x=0.0;y=0.0
for j in i: