def wrapAffine():
img = cv2.imread(Constants.IMG_DIR_TENCENT_TEST + "H.jpg", 0)
img = Util.binaryzation(img)
rows, cols = img.shape
pts1 = np.float32([[0, 0], [0, 20], [20, 0]])
#这样变换会横向变窄
#pts2 = np.float32([[0,0],[0,20],[18,0]])
#这样会纵向变扁
#pts2 = np.float32([[0,0],[0,18],[20,0]])
#这样横向变窄，且有一定的变形
#pts2 = np.float32([[0,0],[0,20],[18,2]])
#这样纵向变窄，且有一定的变形
pts2 = np.float32([[0, 0], [2, 18], [20, 0]])
pts2All = [
np.float32([[0, 0], [0, 20], [18, 0]]),
np.float32([[0, 0], [0, 18], [20, 0]]),
np.float32([[0, 0], [0, 20], [18, 2]]),
np.float32([[0, 0], [2, 18], [20, 0]])
]
#pts2 = np.float32([[0,0],[20,20],[20,0]])
M = cv2.getAffineTransform(pts1, pts2All[0])
print(M)
dst = cv2.warpAffine(~img, M, (cols, rows))
dst = Util.binaryzation(dst)
cv2.imshow("2", img)
cv2.imshow("1", ~dst)
Util.printCV2Image(img)
Util.printCV2Image(~dst)
cv2.waitKey(0)
def convertToBinary():
dir_path = Constants.IMG_DIR_TENCENT_TRAIN + "other/"
for lists in os.listdir(dir_path):
#print(lists)
path = os.path.join(dir_path, lists)
if not os.path.isdir(path):
oriImg = cv2.imread(path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
img = Util.binaryzation(oriImg)
cv2.imwrite(path, img)
def testRotate():
oriImg = cv2.imread(Constants.IMG_DIR_TENCENT_PUZZLE + "mbha.jpg", 0)
img = Util.binaryzation(oriImg)
img = img[:, 0:42]
rows, cols = img.shape
M = cv2.getRotationMatrix2D((cols / 2, rows / 2), -10, 1)
print(M)
dst = cv2.warpAffine(img, M, (cols, rows))
cv2.imshow('img', dst)
cv2.waitKey(0)
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 testAllPoints():
ret = []
labels = []
dir_path = Constants.IMG_DIR_TENCENT_TRAIN
for lists in os.listdir(dir_path):
#print(lists)
path = os.path.join(dir_path, lists)
if not os.path.isdir(path):
oriImg = cv2.imread(path, 0)
img = Util.binaryzation(oriImg)
points, paths = getCornerPointsAndPaths(img)
print("----------------RESULT----------------")
print(path)
print(points)
print(len(paths))
#target = readOneImg(dir_path + "YbUB_39_68_85.jpg")
return ret, labels
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
在这里进行wrap变换应该是最佳的
'''
target = Util.copyOneImg(target, (height, width))
return Util.wrap(target)
#膨胀图像
def dilate(img, element_width):
#OpenCV定义的结构元素
kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(element_width, element_width))
#膨胀图像
dilated = cv2.dilate(~img, kernel)
return ~dilated
if __name__ == "__main__":
fileName = Constants.IMG_DIR_TENCENT_TRAIN + "BSmP_39_54_81.jpg"
readOneImg(fileName)
oriImg = cv2.imread(fileName, 0)
img = Util.binaryzation(oriImg)
#img = Util.erasePaddingInOneChar(img)
img = dilate(img, 7)
img = ~Util.skeleton(img)
cv2.imwrite(Constants.IMG_DIR_TENCENT_TRAIN + "ske2.jpg", img)
#cv2.imshow("ske1",img)
'''path = Constants.IMG_DIR_TENCENT_TRAIN + "VmnZ_31_59_84.jpg"
points, directions = getSpiltPoint(path[path.rindex('/'):])
print(points)
print(directions)
print(directions[0] == Constants.SEARCH_FROM_TOP)'''
cv2.waitKey(0)