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import sys
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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class Point(object):
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def __init__(self, x, y):
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self.x = x
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self.y = y
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def getX(self):
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return self.x
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def getY(self):
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return self.y
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def getGrayDiff(img, currentPoint, tmpPoint): # 获得两点像素之差的绝对值
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return abs(int(img[currentPoint.x, currentPoint.y]) - int(img[tmpPoint.x, tmpPoint.y]))
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def selectConnects(p): # 8邻域或者4邻域
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if p != 0:
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connects = [Point(-1, -1), Point(0, -1), Point(1, -1), Point(1, 0), Point(1, 1), \
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Point(0, 1), Point(-1, 1), Point(-1, 0)]
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else:
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connects = [Point(0, -1), Point(1, 0), Point(0, 1), Point(-1, 0)]
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return connects
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def regionGrow(img_path, x, y, thresh, p):
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img = cv2.imread(img_path, 0) # 读取图片
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height, weight = img.shape
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seedMark = np.zeros(img.shape)
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seedList = []
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seedList.append(Point(x, y))
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label = 1
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connects = selectConnects(p)
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while (len(seedList) > 0):
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currentPoint = seedList.pop(0)
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seedMark[currentPoint.x, currentPoint.y] = label
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for i in range(len(connects)):
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tmpX = currentPoint.x + connects[i].x
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tmpY = currentPoint.y + connects[i].y
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if tmpX < 0 or tmpY < 0 or tmpX >= height or tmpY >= weight:
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continue
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grayDiff = getGrayDiff(img, currentPoint, Point(tmpX, tmpY))
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if grayDiff < thresh and seedMark[tmpX, tmpY] == 0:
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seedMark[tmpX, tmpY] = label
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seedList.append(Point(tmpX, tmpY))
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cv2.imwrite('./output/regionGrow.jpg', seedMark*255)
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'''
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输入：img_path:图片地址
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seeds:初始种子，是一个元素类型为Point的列表，如[ Point(0, -1), Point(1, 0),Point(0, 1), Point(-1, 0)]
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thresh：门限值，两个坐标像素值小于thresh归为一类
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p：等于0算法基于四领域，等于1算法基于八领域
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输出：二值图片，白色部分为初始种子所生长出来的区域，黑色为另一区域
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'''
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if __name__ == '__main__':
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regionGrow(sys.argv[1], eval(sys.argv[2]), eval(sys.argv[3]), eval(sys.argv[4]), eval(sys.argv[5]))
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