###Final Stage###
###
result=""
size=630
size=(size,)*2
number=size[0]/9
print("OCR Stage")
import cv2.cv as cv
import OCR
for i,j in enumerate(b):
ri = i/10
ci = i%10
if ci != 9 and ri!=9:
src = bm[ri:ri+2, ci:ci+2 , :].reshape((4,2))
dst = np.array( [ [ci*number,ri*number],[(ci+1)*number-1,ri*number],[ci*number,(ri+1)*number-1],[(ci+1)*number-1,(ri+1)*number-1] ], np.float32)
retval = cv2.getPerspectiveTransform(src,dst)
warp = cv2.warpPerspective(res2,retval,(size))
whole_digit= warp[ri*number:(ri+1)*number-1 , ci*number:(ci+1)*number-1].copy()
noborder_digit= whole_digit[5:64,5:64]
gray_digit = cv2.cvtColor(noborder_digit,cv2.COLOR_BGR2GRAY)
thresh_digit = cv2.adaptiveThreshold(gray_digit,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,0,151,80)
image = cv.CreateImageHeader((thresh_digit.shape[1],thresh_digit.shape[0]), cv.IPL_DEPTH_8U, 1)
cv.SetData(image, thresh_digit.tostring(), thresh_digit.dtype.itemsize*thresh_digit.shape[1])
result+=OCR.ocr_singledigit(image)
rows = OCR.split_len(result,9)
for row in rows:
print row
print time.time()-st
for row in range(9):
print "\tRow: " + str(row+1)
for column in range(9):
## top left corner = x1:y1 | down right corner = x2:y2
x1,x2,y1,y2 = OCR.getcorners((row,column),r_points)
crop = res2[y1+5 : y2-5 , x1+5 : x2-5]
if crop.size == 0:
result[row][column] = "E"
continue
cv2.imwrite("debug/digits"+str(row)+str(column)+".jpg",crop)
digit = cv2.cv.CreateImageHeader((crop.shape[1],crop.shape[0]), cv2.cv.IPL_DEPTH_8U, 1)
cv2.cv.SetData(digit, crop.tostring(), crop.dtype.itemsize*crop.shape[1])
##recognize the digit
result[column][row] = OCR.ocr_singledigit(digit)
##print out the sudoku puzzle
for row in result:
string = ""
for digit in row:
string+= str(digit) + " "
print string
print
print "Total time: " + str(time.time()-timer_start)
for row in range(9):
print "Row:", row
for column in range(9):
src = bm[row:row+2, column:column+2 , :].reshape((4,2))
dst = np.array( [ [column*sqaure_size,row*sqaure_size],[(column+1)*sqaure_size-1,row*sqaure_size],[column*sqaure_size,(row+1)*sqaure_size-1],[(column+1)*sqaure_size-1,(row+1)*sqaure_size-1] ], np.float32)
retval = cv2.getPerspectiveTransform(src,dst)
warp = cv2.warpPerspective(res2,retval,(size))
whole_digit = warp[row*sqaure_size:(row+1)*sqaure_size-1 , column*sqaure_size:(column+1)*sqaure_size-1].copy()
noborder_digit = whole_digit[5:64,5:64]
gray_digit = cv2.cvtColor(noborder_digit,cv2.COLOR_BGR2GRAY)
thresh_digit = cv2.adaptiveThreshold(gray_digit,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,0,151,80)
image = cv2.cv.CreateImageHeader((thresh_digit.shape[1],thresh_digit.shape[0]), cv2.cv.IPL_DEPTH_8U, 1)
cv2.cv.SetData(image, thresh_digit.tostring(), thresh_digit.dtype.itemsize*thresh_digit.shape[1])
result[row][column] = OCR.ocr_singledigit(image)
for row in row:
row_string = ""
for digit in row:
string += digit + " "
print string
print
print "Total time: " + str(time.time()-timer_start)
print "\t[+]Row: " + str(row + 1)
for column in range(9):
## top left corner = x1:y1 | down right corner = x2:y2
x1, x2, y1, y2 = OCR.getcorners((row, column), R_POINTS)
crop = RES2[y1 + 7 : y2 - 7 , x1 + 7: x2 - 7]
digit = cv2.cv.CreateImageHeader((crop.shape[1], crop.shape[0]), cv2.cv.IPL_DEPTH_8U, 1)
cv2.cv.SetData(digit, crop.tostring(), crop.dtype.itemsize*crop.shape[1])
if DEBUG_MODE:
print row, column
cv2.imwrite(DEBUG_FOLDER + str(row) + str(column)+".jpg", crop)
##recognize the digit
RESULT[column][row] = OCR.ocr_singledigit(digit)
##print out the sudoku puzzle
print
print "[+]Solution:"
for row in RESULT:
string = ""
for digit in row:
string += str(digit) + " "
print string
print
print "Total time: " + str(round(time.time() - TIMER_START, 2)) + " seconds"