我正在尝试从图像中提取轮廓,旋转这些轮廓并将它们插入到新图像中。代码如下。 我的问题在于旋转轮廓方法。执行代码时,会出现以下错误:“TypeError:'cv.cvseq'对象不支持项目分配”。
如何解决这个问题?我正在为Opencv 2.2使用python绑定。
import cv
def rotateContour(contour, centerOfMass, angle):
for index in range(0, len(contour)):
contour[index] = rotatePoint(contour[index], centerOfMass, angle)
return contour
def rotatePoint(point, centerOfMass, angle):
px, py = point
x, y = centerOfMass
temppoint = (px-x, py-y)
temppointx = temppoint[0]*math.cos(angle) + temppoint[1] * math.sin(angle)
temppointy = temppoint[1]*math.cos(angle) - temppoint[0] * math.sin(angle)
temppoint = (temppointx + x, temppointy + y)
return temppoint
inputimage = cv.LoadImage('filename.png', cv.CV_LOAD_IMAGE_GRAYSCALE)
outputimage = cv.CreateImage((10000, 300), 8, 1)
storage = cv.CreateMemStorage (0)
contours = cv.FindContours(inputimage, storage, cv.CV_RETR_EXTERNAL, cv.CV_CHAIN_APPROX_SIMPLE)
for contour in contour_iterator(contours):
gray = cv.CV_RGB(200, 200, 200)
# Rotate contour somehow
contour = rotatecontour(contour)
cv.DrawContours(outputimage, contour, gray, gray, 0, -1, 8)
cv.SaveImage("outputfile.png", outputimage)
答案 0 :(得分:1)
似乎你无法使用Python绑定更改cvseq
对象的元素(注意here用于操作cvseq
对象的Python方法列表只有删除方法序列元素并改变它们的顺序。)
尽管如此,Python绑定仍然提供了实现您在图像中旋转轮廓的既定目标的工具。
由于cv.DrawContours()
方法需要cvseq
作为输入,我们必须在Python中存储和操作轮廓之后找到一些其他的绘制轮廓的方法。一种方法是使用cv.FillPoly()
或cv.DrawPoly()
方法(将元组列表作为输入),具体取决于传递给cv.DrawContours()
的厚度参数是否为-1或>分别为0。
因此,找到轮廓并绘制其旋转对应物的一种方法如下(通过以填充形式重绘并使用OpenCV的矩函数找到每个轮廓的质心):
import cv
import numpy as np
# Draw contour from list of tuples.
def draw_contour( im , contour , color , thickness = 1 , linetype = 8 ,
shift = 0 ) :
if thickness == -1 :
cv.FillPoly( im , [contour] , color , linetype , shift )
else :
cv.PolyLine( im , [contour] , True , color , thickness , linetype , shift )
# Rotate contour around centre point using numpy.
def rotate_contour( contour , centre_point , theta ) :
rotation = np.array( [ [ np.cos( theta ) , -np.sin( theta ) ] ,
[ np.sin( theta ) , np.cos( theta ) ] ] )
centre = np.vstack( [ centre_point ] * len( contour ) )
contour = np.vstack( contour ) - centre
contour = np.dot( contour , rotation ) + centre
return [ tuple ( each_row ) for each_row in contour ]
# Find centre of mass by drawing contour in closed form and using moments.
def find_centre_of_mass( contour ) :
bottom_right = np.max( contour , axis = 0 )
blank = cv.CreateImage( tuple ( bottom_right ) , 8 , 1 )
cv.Set( blank , 0 )
draw_contour( blank , contour , 1, -1 )
moments = cv.Moments( blank , 1 )
sM00 = float ( cv.GetSpatialMoment( moments , 0 , 0 ) )
sM01 = float ( cv.GetSpatialMoment( moments , 0 , 1 ) )
sM10 = float ( cv.GetSpatialMoment( moments , 1 , 0 ) )
return ( sM10 / sM00 , sM01 / sM00 )
THETA = np.pi / 3.0
COLOR = cv.CV_RGB( 200 , 200 , 200 )
input_image = cv.LoadImage( ‘filename.png’ , cv.CV_LOAD_IMAGE_GRAYSCALE )
output_image = cv.CreateImage( ( input_image.width , input_image.height ) ,
input_image.depth , input_image.nChannels )
cv.Set( output_image , 0 )
storage = cv.CreateMemStorage( 0 )
contour_pointer = cv.FindContours( input_image , storage ,
cv.CV_RETR_EXTERNAL ,
cv.CV_CHAIN_APPROX_SIMPLE )
while contour_pointer is not None :
contour = contour_pointer [ : ]
centre_of_mass = find_centre_of_mass( contour )
rotated_contour = rotate_contour( contour , centre_of_mass , THETA )
draw_contour( output_image , rotated_contour , COLOR , -1 )
contour_pointer = contour_pointer.h_next()
cv.SaveImage( ‘outputfile.png’ , output_image)