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OCR-MATH-.py
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OCR-MATH-.py
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import pyautogui
from PIL import Image
import pytesseract
import argparse
from cv2 import cv2
import os
class Screenie:
def __init__(self,name,setregion,path):
self.name = name
self.setregion = setregion
self.path = path
def scshot(self): # screenshot function.
identifiers = [0,0]
image = pyautogui.screenshot(region=self.setregion)
name_new = "{}.png".format(self.name)
path_new = self.path + name_new
image.save(path_new)
identifiers[0] = image
identifiers[1] = path_new
self.path = path_new
self.name = name_new
return identifiers
def imagetext(self):
imagepath = self.path
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--preprocess", type=str, default="thresh",
help="type of preprocessing to be done")
args = vars(ap.parse_args())
image = cv2.imread(imagepath)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
if args["preprocess"] == "thresh":
gray = cv2.threshold(gray, 0, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
elif args["preprocess"] == "blur":
gray = cv2.medianBlur(gray, 3)
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)
# load image as PIL->OCR it-->Delete the temp file.
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
return text
class TextCheck:
def __init__(self,text,bankl,banku,countl,countu,unknown):
self.text = text
self.bankl = bankl
self.banku = banku
self.countl = countl
self.countu = countu
self.unknown = unknown
self.transfer = []
def words(self):
wordlist = self.text.replace("\n"," ")
wordlist = wordlist.split(" ")
pop = []
for i in range(len(wordlist)):
if len(wordlist[i]) == 1:
if not wordlist[i] in self.bankl and not wordlist[i] in self.banku:
pop.append(i)
elif len(wordlist[i]) == 0:
pop.append(i)
wordlist_edit = wordlist
j = 0
k = len(pop)
for i in range(k):
index = (k - 1) - j
wordlist.pop(pop[index])
j = j + 1
return(wordlist_edit,wordlist)
def counting(self):
run_countl = self.countl
run_countu = self.countu
low = filter(str.islower,self.text)
up = filter(str.isupper,self.text)
for char in low:
if char in self.bankl:
index = self.bankl.index(char)
run_countl[index] = 1 + run_countl[index]
elif not char in self.bankl and not char == "," and not char == "." and not char == " " and not char == "\n":
self.unknown.append(char)
else:
pass
for char in up:
if char in self.banku:
index = self.banku.index(char)
run_countu[index] = 1 + run_countu[index]
elif not char in self.banku and not char == "," and not char == "." and not char == " " and not char == "\n":
self.unknown.append(char)
else:
pass
lenl = sum(run_countl)
lenu = sum(run_countu)
out = [run_countl, run_countu, lenl, lenu]
return out
def __iter__(self):
return iter(self.counting())
class Math: #this is all character tracking.
def __init__(self, count_1l, count_2l, count_1u, count_2u,prevoutcome):
self, count_1l, count_2l, count_1u, count_2u,prevoutcome,
self.count_1l = count_1l
self.count_2l = count_2l
self.count_1u = count_1u
self.count_2u = count_2u
self.prevoutcome = prevoutcome
def char_spec_change(self):
y, Y = 0,0
z, Z = 0,0
n, N = 0,0
zn, Zn = 0,0
outcome = 0
sl1 = sum(self.count_1l)
su1 = sum(self.count_1u)
sl2 = sum(self.count_2l)
su2 = sum(self.count_2u)
for i in self.count_1l:
if i == self.count_2l[n]:
n = n + 1
elif i > self.count_2l[n]:
y = y + 1
n = n + 1
elif i < self.count_2l[n]:
zn = zn + (self.count_2l[n]-i)
z = z + 1
n = n + 1
for j in self.count_1u:
if j == self.count_2u[N]:
N = N + 1
elif j > self.count_2u[N]:
Y = Y + 1
N = N + 1
elif j < self.count_2u[N]:
Zn = Zn + (self.count_2u[N]-j)
Z = Z + 1
N = N + 1
#y: from 1->2 the instances decreased
#z: from 1->2 the instances increased
if sl2 and su2 == 0:
outcome = 3
cause = '0 char in string'
elif not outcome == 3:
if Y > 0 or y > 3: #loss (uppercase)
if sl2 == 0:
outcome = 3 #repeat
cause = ['prevented loss threshold mislabing', (y, Y), (z, Z), (n, N), (zn, Zn)]
else:
outcome = 0 #new
cause = ['first loss threshold', (y, Y), (z, Z), (n, N), (zn, Zn)]
else:
if zn > 0 or Zn > 0: #gain
if y > 3 or Y > 0: #gain -> loss
outcome = 0 #new
cause = ['gain --> loss', (y, Y), (z, Z), (n, N), (zn, Zn)]
elif y < 4 and Y == 0: #gain -> no loss
if self.prevoutcome == 3: #gain after outcome 3
outcome = 0 #new
cause = ['gained after an o:3 skip', (y, Y), (z, Z), (n, N), (zn, Zn)]
elif not self.prevoutcome == 3:
outcome = 1 #same
cause = ['gain --> no loss', (y, Y), (z, Z), (n, N), (zn, Zn)]
outcome = 0 #new
else:
outcome = 4
cause = ['error inside 1', (y, Y), (z, Z), (n, N), (zn, Zn)]
elif zn == 0 or Zn == 0: #no gain
if y > 3 or Y > 0: #no gain -> loss
outcome = 0 #new
cause = ['no gain --> loss', (y, Y), (z, Z), (n, N), (zn, Zn)]
elif y < 4 and Y == 0: #no gain --> no loss
if self.prevoutcome == 3: #no gain no loss after outcome 3
outcome = 3 #repeat
cause = ['no gain/no loss after outcome 3', (y, Y), (z, Z), (n, N), (zn, Zn)]
elif not self.prevoutcome == 3:
outcome = 1 #same
cause = ['no gain --> no loss', (y, Y), (z, Z), (n, N), (zn, Zn)]
else:
outcome = 4
cause = ["error inside 2", (y, Y), (z, Z), (n, N), (zn, Zn)]
elif zn < 0 or Zn < 0:
outcome = 3
cause = 'prevented negative zn error'
elif y == 0 and z == 0 and Y == 0 and Z == 0:
outcome = 1
cause = '0,0,0,0'
else:
outcome = 4
cause = ["error outside", (y, Y), (z, Z), (n, N), (zn, Zn)]
h = (sl1,su1)
g = (sl2, su2)
return outcome, cause, h,g,self.prevoutcome
def __iter__(self):
return iter(self.char_spec_change())
class NotMath:
def __init__(self, word1, word2):
self.word1 = word1
self.word2 = word2
def wordchange(self):
nonmatch = [x for x in self.word1 + self.word2 if x not in self.word1 or x not in self.word2]
if not nonmatch:
return 'same'
else:
if self.word1 and self.word2 == []:
return 'double empty lists?'
elif self.word1 == []:
return 'empty list 1'
elif self.word2 == []:
return 'empty list 2'
else:
return nonmatch
class Saves:
def __init__(self,path_current,folder_new,title):
self.path_current = path_current
self.folder_new = folder_new
self.title = title
def moving(self):
path_new = self.folder_new + self.title
os.rename(self.path_current, path_new)
return path_new
def __str__(self):
return str('saved new image at:\n%s' % self.moving())