| commit | author | age | ||
| e555c0 | 1 | from pyzbar.pyzbar import decode |
| 9efc18 | 2 | from sid_process import enhanceSID |
| e555c0 | 3 | import cv2 |
| SP | 4 | import numpy as np |
| 5 | import math | |
| 6 | ||
| 7 | ||
| 511c2e | 8 | class Paper: |
| SP | 9 | def __init__(self, filename=None): |
| 10 | self.filename = filename | |
| 11 | self.invalid = None | |
| 12 | self.QRData = None | |
| 13 | self.errors = [] | |
| 14 | self.warnings = [] | |
| 15 | if filename is not None: | |
| 16 | self.loadImage(filename) | |
| 17 | self.runOcr() | |
| e555c0 | 18 | |
| 511c2e | 19 | def loadImage(self, filename, rgbchannel=0): |
| SP | 20 | self.img = cv2.imread(filename, rgbchannel) |
| 21 | if self.img is None: | |
| 22 | self.errors.append("File could not be loaded!") | |
| 23 | self.invalid = True | |
| 24 | return | |
| 25 | self.imgHeight, self.imgWidth = self.img.shape[0:2] | |
| e555c0 | 26 | |
| 511c2e | 27 | def saveImage(self, filename="debug_image.png"): |
| SP | 28 | cv2.imwrite(filename, self.img) |
| e555c0 | 29 | |
| 511c2e | 30 | def runOcr(self): |
| SP | 31 | if self.invalid == True: |
| 32 | return | |
| 33 | self.decodeQRandRotate() | |
| 34 | self.imgTreshold() | |
| 35 | skewAngle = 0 | |
| 36 | # try: | |
| 37 | # skewAngle=self.getSkewAngle() | |
| 38 | # except: | |
| 39 | # self.errors.append("Could not determine skew angle!") | |
| 40 | # self.rotateAngle(skewAngle) | |
| e555c0 | 41 | |
| 511c2e | 42 | self.generateAnswerMatrix() |
| e555c0 | 43 | |
| 511c2e | 44 | self.saveImage() |
| e555c0 | 45 | |
| 511c2e | 46 | def decodeQRandRotate(self): |
| SP | 47 | if self.invalid == True: |
| 48 | return | |
| 49 | blur = cv2.blur(self.img, (3, 3)) | |
| 50 | d = decode(blur) | |
| 51 | self.img = blur | |
| 52 | if len(d) == 0: | |
| 53 | self.errors.append("QR code could not be found!") | |
| 54 | self.data = None | |
| 55 | self.invalid = True | |
| 56 | return | |
| 57 | self.QRDecode = d | |
| 58 | self.QRData = d[0].data | |
| 59 | xpos = d[0].rect.left | |
| 60 | ypos = d[0].rect.top | |
| 61 | # check if image is rotated wrongly | |
| 62 | if xpos > self.imgHeight / 2.0 and ypost > self.imgWidth / 2.0: | |
| 63 | self.rotateAngle(180) | |
| e555c0 | 64 | |
| 511c2e | 65 | def rotateAngle(self, angle=0): |
| SP | 66 | rot_mat = cv2.getRotationMatrix2D( |
| 67 | (self.imgHeight / 2, self.imgWidth / 2), angle, 1.0 | |
| 68 | ) | |
| 69 | result = cv2.warpAffine( | |
| 70 | self.img, | |
| 71 | rot_mat, | |
| 72 | (self.imgHeight, self.imgWidth), | |
| 73 | flags=cv2.INTER_CUBIC, | |
| 74 | borderMode=cv2.BORDER_CONSTANT, | |
| 75 | borderValue=(255, 255, 255), | |
| 76 | ) | |
| e555c0 | 77 | |
| 511c2e | 78 | self.img = result |
| SP | 79 | self.imgHeight, self.imgWidth = self.img.shape[0:2] |
| e555c0 | 80 | |
| 511c2e | 81 | # todo, make better tresholding |
| e555c0 | 82 | |
| 511c2e | 83 | def imgTreshold(self): |
| SP | 84 | (self.thresh, self.bwimg) = cv2.threshold( |
| 85 | self.img, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU | |
| 86 | ) | |
| e555c0 | 87 | |
| 511c2e | 88 | def getSkewAngle(self): |
| SP | 89 | neg = 255 - self.bwimg # get negative image |
| 90 | cv2.imwrite("debug_1.png", neg) | |
| e555c0 | 91 | |
| 511c2e | 92 | angle_counter = 0 # number of angles |
| SP | 93 | angle = 0.0 # collects sum of angles |
| 94 | cimg = cv2.cvtColor(self.img, cv2.COLOR_GRAY2BGR) | |
| e555c0 | 95 | |
| 511c2e | 96 | # get all the Hough lines |
| SP | 97 | for line in cv2.HoughLinesP(neg, 1, np.pi / 180, 325): |
| 98 | x1, y1, x2, y2 = line[0] | |
| 99 | cv2.line(cimg, (x1, y1), (x2, y2), (0, 0, 255), 2) | |
| 100 | # calculate the angle (in radians) | |
| 101 | this_angle = np.arctan2(y2 - y1, x2 - x1) | |
| 102 | if this_angle and abs(this_angle) <= 10: | |
| 103 | # filtered zero degree and outliers | |
| 104 | angle += this_angle | |
| 105 | angle_counter += 1 | |
| e555c0 | 106 | |
| 511c2e | 107 | # the skew is calculated of the mean of the total angles, #try block helps with division by zero. |
| SP | 108 | try: |
| 109 | skew = np.rad2deg( | |
| 110 | angle / angle_counter | |
| 111 | ) # the 1.2 factor is just experimental.... | |
| 112 | except: | |
| 113 | skew = 0 | |
| e555c0 | 114 | |
| 511c2e | 115 | cv2.imwrite("debug_2.png", cimg) |
| SP | 116 | return skew |
| e555c0 | 117 | |
| 511c2e | 118 | def locateUpMarkers(self, threshold=0.85, height=200): |
| SP | 119 | template = cv2.imread("template.png", 0) |
| 120 | w, h = template.shape[::-1] | |
| 121 | crop_img = self.img[0:height, :] | |
| 122 | res = cv2.matchTemplate(crop_img, template, cv2.TM_CCOEFF_NORMED) | |
| 123 | loc = np.where(res >= threshold) | |
| 124 | cimg = cv2.cvtColor(crop_img, cv2.COLOR_GRAY2BGR) | |
| 125 | # remove false matching of the squares in qr code | |
| 126 | loc_filtered_x = [] | |
| 127 | loc_filtered_y = [] | |
| 128 | if len(loc[0]) == 0: | |
| 129 | min_y = -1 | |
| 130 | else: | |
| 131 | min_y = np.min(loc[0]) | |
| 132 | for pt in zip(*loc[::-1]): | |
| 133 | if pt[1] < min_y + 20: | |
| 134 | loc_filtered_y.append(pt[1]) | |
| 135 | loc_filtered_x.append(pt[0]) | |
| 136 | # order by x coordinate | |
| 137 | loc_filtered_x, loc_filtered_y = zip( | |
| 138 | *sorted(zip(loc_filtered_x, loc_filtered_y)) | |
| 139 | ) | |
| 140 | # loc=[loc_filtered_y,loc_filtered_x] | |
| 141 | # remove duplicates | |
| 142 | a = np.diff(loc_filtered_x) > 40 | |
| 143 | a = np.append(a, True) | |
| 144 | loc_filtered_x = np.array(loc_filtered_x) | |
| 145 | loc_filtered_y = np.array(loc_filtered_y) | |
| 146 | loc = [loc_filtered_y[a], loc_filtered_x[a]] | |
| 147 | for pt in zip(*loc[::-1]): | |
| 148 | cv2.rectangle(cimg, pt, (pt[0] + w, pt[1] + h), (0, 255, 255), 2) | |
| e555c0 | 149 | |
| 511c2e | 150 | cv2.imwrite("debug_3.png", cimg) |
| e555c0 | 151 | |
| 511c2e | 152 | self.xMarkerLocations = loc |
| SP | 153 | return loc |
| e555c0 | 154 | |
| 511c2e | 155 | def locateRightMarkers(self, threshold=0.85, width=200): |
| SP | 156 | template = cv2.imread("template.png", 0) |
| 157 | w, h = template.shape[::-1] | |
| 158 | crop_img = self.img[:, -width:] | |
| 159 | res = cv2.matchTemplate(crop_img, template, cv2.TM_CCOEFF_NORMED) | |
| 160 | loc = np.where(res >= threshold) | |
| 161 | cimg = cv2.cvtColor(crop_img, cv2.COLOR_GRAY2BGR) | |
| 162 | # remove false matching of the squares in qr code | |
| 163 | loc_filtered_x = [] | |
| 164 | loc_filtered_y = [] | |
| 165 | if len(loc[1]) == 0: | |
| 166 | min_x = -1 | |
| 167 | else: | |
| 168 | max_x = np.max(loc[1]) | |
| 169 | for pt in zip(*loc[::-1]): | |
| 170 | if pt[1] > max_x - 20: | |
| 171 | loc_filtered_y.append(pt[1]) | |
| 172 | loc_filtered_x.append(pt[0]) | |
| 173 | # order by y coordinate | |
| 174 | loc_filtered_y, loc_filtered_x = zip( | |
| 175 | *sorted(zip(loc_filtered_y, loc_filtered_x)) | |
| 176 | ) | |
| 177 | # loc=[loc_filtered_y,loc_filtered_x] | |
| 178 | # remove duplicates | |
| 179 | a = np.diff(loc_filtered_y) > 40 | |
| 180 | a = np.append(a, True) | |
| 181 | loc_filtered_x = np.array(loc_filtered_x) | |
| 182 | loc_filtered_y = np.array(loc_filtered_y) | |
| 183 | loc = [loc_filtered_y[a], loc_filtered_x[a]] | |
| 184 | for pt in zip(*loc[::-1]): | |
| 185 | cv2.rectangle(cimg, pt, (pt[0] + w, pt[1] + h), (0, 255, 255), 2) | |
| e555c0 | 186 | |
| 511c2e | 187 | cv2.imwrite("debug_4.png", cimg) |
| e555c0 | 188 | |
| 511c2e | 189 | self.yMarkerLocations = [loc[0], loc[1] + self.imgWidth - width] |
| SP | 190 | return self.yMarkerLocations |
| e555c0 | 191 | |
| 511c2e | 192 | def generateAnswerMatrix(self): |
| SP | 193 | self.locateUpMarkers() |
| 194 | self.locateRightMarkers() | |
| e555c0 | 195 | |
| 511c2e | 196 | roixoff = 10 |
| SP | 197 | roiyoff = 5 |
| 198 | roiwidth = 50 | |
| 199 | roiheight = roiwidth | |
| 200 | totpx = roiwidth * roiheight | |
| e555c0 | 201 | |
| 511c2e | 202 | self.answerMatrix = [] |
| SP | 203 | for y in self.yMarkerLocations[0]: |
| 204 | oneline = [] | |
| 205 | for x in self.xMarkerLocations[1]: | |
| 206 | roi = self.bwimg[ | |
| 207 | y - roiyoff : y + int(roiheight - roiyoff), | |
| 208 | x - roixoff : x + int(roiwidth - roixoff), | |
| 209 | ] | |
| 210 | # cv2.imwrite('ans_x'+str(x)+'_y_'+str(y)+'.png',roi) | |
| 211 | black = totpx - cv2.countNonZero(roi) | |
| 212 | oneline.append(black / totpx) | |
| 213 | self.answerMatrix.append(oneline) | |
| 9efc18 | 214 | |
| SP | 215 | def get_enhanced_sid(self): |
| 216 | es= enhanceSID(self.img[int(0.04*self.imgHeight):int(0.08*self.imgHeight), int(0.7*self.imgWidth):int(0.99*self.imgWidth)]) | |
| 217 | cv2.imwrite("enhancedSID.png",es) | |
