def xihua():
for lists in os.listdir(Constants.IMG_DIR_TENCENT_TRAIN):
#print(lists)
path = os.path.join(Constants.IMG_DIR_TENCENT_TRAIN, lists)
if not os.path.isdir(path):
print(path)
oriImg = cv2.imread(path, 0)
img = Util.binaryzation(oriImg)
img = Util.erasePaddingInOneChar(img)
#cv2.imshow("ori", img)
#height, width = img.shape
img = ~Util.skeleton(~img)
cv2.imwrite(path, img)
#ret.append(readOneImg(path))
pass
def readOneImg(path):
oriImg = cv2.imread(path, 0)
img = Util.binaryzation(oriImg)
img = Util.erasePaddingInOneChar(img)
height, width = img.shape
#获取指定的三个分割点, 再根据分割点做分割线
points, directions = getSpiltPoint(path[path.rindex('/'):])
path1 = Util.fillPath(SpiltUtil.spiltOne(img, points[0], directions[0], 0), height)
path2 = Util.fillPath(SpiltUtil.spiltOne(img, points[1], directions[1], 1), height)
path3 = Util.fillPath(SpiltUtil.spiltOne(img, points[2], directions[2], 2), height)
path0 = Util.getLeftBorder(height)
path4 = Util.getRightBoder(width, height)
ret = []
ret.extend(Util.conventToTrainCharFromAllWrap(getOneChar(img, path0, path1)))
ret.extend(Util.conventToTrainCharFromAllWrap(getOneChar(img, path1, path2)))
ret.extend(Util.conventToTrainCharFromAllWrap(getOneChar(img, path2, path3)))
ret.extend(Util.conventToTrainCharFromAllWrap(getOneChar(img, path3, path4)))
return ret
def readInput(svm, puzzle):
oriImg = cv2.imread(puzzle, 0)
img = Util.binaryzation(oriImg)
img = Util.erasePaddingInOneChar(img)
points, paths = SpiltUseBackground.getCornerPointsAndPaths(img)
print("-------RECOGNISE--------")
print(points)
print("paths:")
for p in paths:
print(p)
height, width = img.shape
code = []
#p1 = [23:39]
path0 = Util.getLeftBorder(height)
good_path, result = recogniseOne(svm, img, path0, paths, 0)
print("First split point:" + str(good_path[0][0]) + " result:" +
chr(svm.classes_[result] + ord('A')))
code.append(chr(svm.classes_[result] + ord('A')))
#path0 = Util.fillPath(SpiltUseCV2.spiltOne(img, p1), height)
good_path, result = recogniseOne(svm, img, good_path, paths, 1)
print("Second split point:" + str(good_path[0][0]) + " result:" +
chr(svm.classes_[result] + ord('A')))
code.append(chr(svm.classes_[result] + ord('A')))
#path0 = Util.fillPath(SpiltUseCV2.spiltOne(img, p2), height)
good_path, result = recogniseOne(svm, img, good_path, paths, 2)
print("Third split point:" + str(good_path[0][0]) + " result:" +
chr(svm.classes_[result] + ord('A')))
code.append(chr(svm.classes_[result] + ord('A')))
#path0 = Util.fillPath(SpiltUseCV2.spiltOne(img, p3), height)
good_path, result = recogniseOne(svm, img, good_path, paths, 3)
print("Fourth split point:" + str(good_path[0][0]) + " result:" +
chr(svm.classes_[result] + ord('A')))
code.append(chr(svm.classes_[result] + ord('A')))
print("Result:" + str(code))
return code
def spiltOne(img, startX, direction, charIndex):
#for j in range(startX, endX):
height, width = img.shape
path = []
img = Util.erasePaddingInOneChar(img)
img = ~Util.skeleton(~img)
#Util.printCV2Image(img)
#cv2.imshow("1", img)
if direction == Constants.SEARCH_FROM_TOP:
print("direction: t")
path.append((startX, 0))
searchOnceFromTop(img, path, startX, 0, charIndex)
else:
print("direction: b")
path.append((startX, height - 1))
searchOnceFromBottom(img, path, startX, height - 1, charIndex)
#print(path)
#for i in range(len(path.path) - 1):
# cv2.line(img, path.paths[i].toTuple(), path.paths[i - 1].toTuple(), 0)
#cv2.imshow("Image", img)
#if we want show a img, must add this
#cv2.waitKey (0)
return path
def erasePaddingInAllChar(target):
for img in target:
for char in img:
char = Util.erasePaddingInOneChar(char)
#膨胀图像
def dilate(img):
#OpenCV定义的结构元素
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
#膨胀图像
dilated = cv2.dilate(img, kernel)
return dilated
if __name__ == "__main__":
#xihua()
oriImg = cv2.imread(
Constants.IMG_DIR_TENCENT_TRAIN + "AANV_39b_58b_82b.jpg", 0)
img = Util.binaryzation(oriImg)
#img = dilate(~img)
img = Util.erasePaddingInOneChar(img)
#img = Util.binaryzation(oriImg)
#img = ~Util.skeleton(~img)
cv2.imwrite(Constants.IMG_DIR_TENCENT_TRAIN + "1.jpg", img)
'''img = cv2.imread(Constants.IMG_DIR_TENCENT_PUZZLE + "mbha.jpg")
im = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
im = cv2.threshold(im, 0, 255, cv2.THRESH_OTSU)[1]
im[im == 255] = 1
im = morphology.skeletonize(im)
im = im.astype(np.uint8)
im[im == 1] = 255
cv2.imshow("Image1", im)
cv2.imshow("Image2", img)
im[im == 255] = 1
