def _extractData(self,seq,color,minsize,maxsize):
"""
Extract the bulk of the data from a give blob. If the blob's are is too large
or too small the method returns none.
"""
if( seq is None or not len(seq)):
return None
area = cv.ContourArea(seq)
if( area < minsize or area > maxsize):
return None
retVal = Blob()
retVal.image = color
retVal.mArea = area
retVal.mMinRectangle = cv.MinAreaRect2(seq)
bb = cv.BoundingRect(seq)
retVal.x = bb[0]+(bb[2]/2)
retVal.y = bb[1]+(bb[3]/2)
retVal.mPerimeter = cv.ArcLength(seq)
if( seq is not None): #KAS
retVal.mContour = list(seq)
#retVal.points = list(seq) KAS 4/30
# so this is a bit hacky....
# For blobs that live right on the edge of the image OpenCV reports the position and width
# height as being one over for the true position. E.g. if a blob is at (0,0) OpenCV reports
# its position as (1,1). Likewise the width and height for the other corners is reported as
# being one less than the width and height. This is a known bug.
xx = bb[0]
yy = bb[1]
ww = bb[2]
hh = bb[3]
retVal.points = [(xx,yy),(xx+ww,yy),(xx+ww,yy+hh),(xx,yy+hh)]
retVal._updateExtents()
chull = cv.ConvexHull2(seq,cv.CreateMemStorage(),return_points=1)
retVal.mConvexHull = list(chull)
hullMask = self._getHullMask(chull,bb)
retVal.mHullImg = self._getBlobAsImage(chull,bb,color.getBitmap(),hullMask)
retVal.mHullMask = Image(hullMask)
del chull
moments = cv.Moments(seq)
#This is a hack for a python wrapper bug that was missing
#the constants required from the ctype
retVal.m00 = area
try:
retVal.m10 = moments.m10
retVal.m01 = moments.m01
retVal.m11 = moments.m11
retVal.m20 = moments.m20
retVal.m02 = moments.m02
retVal.m21 = moments.m21
retVal.m12 = moments.m12
except:
retVal.m10 = cv.GetSpatialMoment(moments,1,0)
retVal.m01 = cv.GetSpatialMoment(moments,0,1)
retVal.m11 = cv.GetSpatialMoment(moments,1,1)
retVal.m20 = cv.GetSpatialMoment(moments,2,0)
retVal.m02 = cv.GetSpatialMoment(moments,0,2)
retVal.m21 = cv.GetSpatialMoment(moments,2,1)
retVal.m12 = cv.GetSpatialMoment(moments,1,2)
retVal.mHu = cv.GetHuMoments(moments)
mask = self._getMask(seq,bb)
retVal.mMask = Image(mask)
retVal.mAvgColor = self._getAvg(color.getBitmap(),bb,mask)
retVal.mAvgColor = retVal.mAvgColor[0:3]
#retVal.mAvgColor = self._getAvg(color.getBitmap(),retVal.mBoundingBox,mask)
#retVal.mAvgColor = retVal.mAvgColor[0:3]
retVal.mImg = self._getBlobAsImage(seq,bb,color.getBitmap(),mask)
retVal.mHoleContour = self._getHoles(seq)
retVal.mAspectRatio = retVal.mMinRectangle[1][0]/retVal.mMinRectangle[1][1]
return retVal
def _extractData(self,seq,color,minsize,maxsize):
"""
Extract the bulk of the data from a give blob. If the blob's are is too large
or too small the method returns none.
"""
if( seq is None or not len(seq)):
return None
area = cv.ContourArea(seq)
if( area < minsize or area > maxsize):
return None
retVal = Blob()
retVal.image = color
retVal.mArea = area
retVal.mMinRectangle = cv.MinAreaRect2(seq)
retVal.mBoundingBox = cv.BoundingRect(seq)
retVal.x = retVal.mBoundingBox[0]+(retVal.mBoundingBox[2]/2)
retVal.y = retVal.mBoundingBox[1]+(retVal.mBoundingBox[3]/2)
retVal.mPerimeter = cv.ArcLength(seq)
if( seq is not None): #KAS
retVal.mContour = list(seq)
retVal.points = list(seq)
# so this is a bit hacky.... need to refactor blobs
xx = retVal.mBoundingBox[0]
yy = retVal.mBoundingBox[1]
ww = retVal.mBoundingBox[2]
hh = retVal.mBoundingBox[3]
retVal.boundingBox = [(xx,yy),(xx+ww,yy),(xx+ww,yy+hh),(xx,yy+hh)]
chull = cv.ConvexHull2(seq,cv.CreateMemStorage(),return_points=1)
retVal.mConvexHull = list(chull)
hullMask = self._getHullMask(chull,retVal.mBoundingBox)
retVal.mHullImg = self._getBlobAsImage(chull,retVal.mBoundingBox,color.getBitmap(),hullMask)
retVal.mHullMask = Image(hullMask)
del chull
moments = cv.Moments(seq)
#This is a hack for a python wrapper bug that was missing
#the constants required from the ctype
retVal.m00 = area
try:
retVal.m10 = moments.m10
retVal.m01 = moments.m01
retVal.m11 = moments.m11
retVal.m20 = moments.m20
retVal.m02 = moments.m02
retVal.m21 = moments.m21
retVal.m12 = moments.m12
except:
retVal.m10 = cv.GetSpatialMoment(moments,1,0)
retVal.m01 = cv.GetSpatialMoment(moments,0,1)
retVal.m11 = cv.GetSpatialMoment(moments,1,1)
retVal.m20 = cv.GetSpatialMoment(moments,2,0)
retVal.m02 = cv.GetSpatialMoment(moments,0,2)
retVal.m21 = cv.GetSpatialMoment(moments,2,1)
retVal.m12 = cv.GetSpatialMoment(moments,1,2)
retVal.mHu = cv.GetHuMoments(moments)
mask = self._getMask(seq,retVal.mBoundingBox)
retVal.mMask = Image(mask)
retVal.mAvgColor = self._getAvg(color.getBitmap(),retVal.mBoundingBox,mask)
retVal.mAvgColor = retVal.mAvgColor[0:3]
#retVal.mAvgColor = self._getAvg(color.getBitmap(),retVal.mBoundingBox,mask)
#retVal.mAvgColor = retVal.mAvgColor[0:3]
retVal.mImg = self._getBlobAsImage(seq,retVal.mBoundingBox,color.getBitmap(),mask)
retVal.mHoleContour = self._getHoles(seq)
retVal.mAspectRatio = retVal.mMinRectangle[1][0]/retVal.mMinRectangle[1][1]
return retVal
