from pyzbar.pyzbar import decode
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import cv2
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import numpy as np
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import math
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class Paper():
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def __init__(self, filename=None):
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self.filename=filename
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self.invalid=None
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self.QRData=None
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self.errors=[]
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self.warnings=[]
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if filename is not None:
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self.loadImage(filename)
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self.runOcr()
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def loadImage(self, filename, rgbchannel=0):
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self.img=cv2.imread(filename,rgbchannel)
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if self.img is None:
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self.errors.append("File could not be loaded!")
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self.invalid=True
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return
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self.imgHeight, self.imgWidth = self.img.shape[0:2]
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def saveImage(self, filename='debug_image.png'):
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cv2.imwrite(filename, self.img)
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def runOcr(self):
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if self.invalid==True:
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return
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self.decodeQRandRotate()
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self.imgTreshold()
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skewAngle=0
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# try:
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# skewAngle=self.getSkewAngle()
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# except:
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# self.errors.append("Could not determine skew angle!")
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# self.rotateAngle(skewAngle)
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self.generateAnswerMatrix()
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self.saveImage()
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def decodeQRandRotate(self):
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if self.invalid == True:
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return
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blur = cv2.blur(self.img,(3,3))
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d=decode(blur)
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self.img=blur
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if len(d) == 0:
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self.errors.append("QR code could not be found!")
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self.data=None
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self.invalid=True
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return
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self.QRDecode=d
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self.QRData=d[0].data
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xpos=d[0].rect.left
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ypos=d[0].rect.top
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#check if image is rotated wrongly
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if xpos>self.imgHeight/2.0 and ypost>self.imgWidth/2.0:
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self.rotate(180)
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def rotateAngle(self,angle=0):
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rot_mat = cv2.getRotationMatrix2D((self.imgHeight/2, self.imgWidth/2), angle, 1.0)
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result = cv2.warpAffine(self.img,
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rot_mat,
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(self.imgHeight, self.imgWidth),
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flags=cv2.INTER_CUBIC,
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borderMode=cv2.BORDER_CONSTANT,
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borderValue=(255, 255, 255))
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self.img=result
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self.imgHeight, self.imgWidth = self.img.shape[0:2]
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#todo, make better tresholding
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def imgTreshold(self):
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(self.thresh, self.bwimg) = cv2.threshold(self.img, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
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def getSkewAngle(self):
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neg = 255 - self.bwimg # get negative image
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cv2.imwrite('debug_1.png', neg)
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angle_counter = 0 # number of angles
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angle = 0.0 # collects sum of angles
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cimg = cv2.cvtColor(self.img,cv2.COLOR_GRAY2BGR)
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# get all the Hough lines
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for line in cv2.HoughLinesP(neg, 1, np.pi/180, 325):
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x1, y1, x2, y2 = line[0]
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cv2.line(cimg,(x1,y1), (x2,y2), (0,0,255),2)
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# calculate the angle (in radians)
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this_angle = np.arctan2(y2 - y1, x2 - x1)
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if this_angle and abs(this_angle) <= 10:
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# filtered zero degree and outliers
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angle += this_angle
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angle_counter += 1
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# the skew is calculated of the mean of the total angles, #try block helps with division by zero.
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try:
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skew = np.rad2deg(angle / angle_counter) #the 1.2 factor is just experimental....
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except:
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skew=0
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cv2.imwrite('debug_2.png',cimg)
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return skew
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def locateUpMarkers(self, threshold=0.8, height=200):
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template = cv2.imread('template.png',0)
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w, h = template.shape[::-1]
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crop_img = self.img[0:height, :]
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res = cv2.matchTemplate(crop_img,template,cv2.TM_CCOEFF_NORMED)
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loc = np.where( res >= threshold)
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cimg = cv2.cvtColor(crop_img,cv2.COLOR_GRAY2BGR)
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#remove false matching of the squares in qr code
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loc_filtered_x=[]
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loc_filtered_y=[]
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min_y=np.min(loc[0])
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for pt in zip(*loc[::-1]):
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if(pt[1]<min_y+20):
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loc_filtered_y.append(pt[1])
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loc_filtered_x.append(pt[0])
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#order by x coordinate
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loc_filtered_x,loc_filtered_y = zip(*sorted(zip(loc_filtered_x, loc_filtered_y)))
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#loc=[loc_filtered_y,loc_filtered_x]
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#remove duplicates
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a=np.diff(loc_filtered_x)>40
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a=np.append(a,True)
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loc_filtered_x=np.array(loc_filtered_x)
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loc_filtered_y=np.array(loc_filtered_y)
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loc=[loc_filtered_y[a],loc_filtered_x[a]]
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for pt in zip(*loc[::-1]):
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cv2.rectangle(cimg, pt, (pt[0] + w, pt[1] + h), (0,255,255), 2)
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cv2.imwrite('debug_3.png',cimg)
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self.xMarkerLocations=loc
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return loc
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def locateRightMarkers(self, threshold=0.8, width=200):
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template = cv2.imread('template.png',0)
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w, h = template.shape[::-1]
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crop_img = self.img[:, -width:]
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res = cv2.matchTemplate(crop_img,template,cv2.TM_CCOEFF_NORMED)
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loc = np.where( res >= threshold)
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cimg = cv2.cvtColor(crop_img,cv2.COLOR_GRAY2BGR)
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#remove false matching of the squares in qr code
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loc_filtered_x=[]
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loc_filtered_y=[]
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max_x=np.max(loc[1])
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for pt in zip(*loc[::-1]):
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if(pt[1]>max_x-20):
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loc_filtered_y.append(pt[1])
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loc_filtered_x.append(pt[0])
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#order by y coordinate
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loc_filtered_y,loc_filtered_x = zip(*sorted(zip(loc_filtered_y, loc_filtered_x)))
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#loc=[loc_filtered_y,loc_filtered_x]
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#remove duplicates
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a=np.diff(loc_filtered_y)>40
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a=np.append(a,True)
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loc_filtered_x=np.array(loc_filtered_x)
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loc_filtered_y=np.array(loc_filtered_y)
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loc=[loc_filtered_y[a],loc_filtered_x[a]]
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for pt in zip(*loc[::-1]):
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cv2.rectangle(cimg, pt, (pt[0] + w, pt[1] + h), (0,255,255), 2)
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cv2.imwrite('debug_4.png',cimg)
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self.yMarkerLocations=[loc[0], loc[1]+self.imgWidth-width]
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return self.yMarkerLocations
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def generateAnswerMatrix(self):
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self.locateUpMarkers()
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self.locateRightMarkers()
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roixoff=10
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roiyoff=5
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roiwidth=50
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roiheight=roiwidth
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totpx=roiwidth*roiheight
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self.answerMatrix=[]
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for y in self.yMarkerLocations[0]:
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oneline=[]
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for x in self.xMarkerLocations[1]:
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roi=self.bwimg[ y-roiyoff:y+int(roiheight-roiyoff),x-roixoff:x+int(roiwidth-roixoff)]
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#cv2.imwrite('ans_x'+str(x)+'_y_'+str(y)+'.png',roi)
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black=totpx-cv2.countNonZero(roi)
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oneline.append(black/totpx)
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self.answerMatrix.append(oneline)
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