class ColorSegmentation(SegmentationBase):
"""
Perform color segmentation based on a color model or color provided. This class
uses ColorModel.py to create a color model.
"""
mColorModel = []
mError = False
mCurImg = []
mTruthImg = []
mBlobMaker = []
def __init__(self):
self.mColorModel = ColorModel()
self.mError = False
self.mCurImg = Image()
self.mTruthImg = Image()
self.mBlobMaker = BlobMaker()
def addImage(self, img):
"""
Add a single image to the segmentation algorithm
"""
self.mTruthImg = img
self.mCurImg = self.mColorModel.threshold(img)
return
def isReady(self):
"""
Returns true if the camera has a segmented image ready.
"""
return True;
def isError(self):
"""
Returns true if the segmentation system has detected an error.
Eventually we'll consruct a syntax of errors so this becomes
more expressive
"""
return self.mError #need to make a generic error checker
def resetError(self):
"""
Clear the previous error.
"""
self.mError = false
return
def reset(self):
"""
Perform a reset of the segmentation systems underlying data.
"""
self.mColorModel.reset()
def getRawImage(self):
"""
Return the segmented image with white representing the foreground
and black the background.
"""
return self.mCurImg
def getSegmentedImage(self, whiteFG=True):
"""
Return the segmented image with white representing the foreground
and black the background.
"""
return self.mCurImg
def getSegmentedBlobs(self):
"""
return the segmented blobs from the fg/bg image
"""
return self.mBlobMaker.extractFromBinary(self.mCurImg,self.mTruthImg)
# The following are class specific methods
def addToModel(self, data):
self.mColorModel.add(data)
def subtractModel(self, data):
self.mColorModel.remove(data)
def __getstate__(self):
mydict = self.__dict__.copy()
self.mBlobMaker = None
del mydict['mBlobMaker']
return mydict
def __setstate__(self, mydict):
self.__dict__ = mydict
self.mBlobMaker = BlobMaker()
class ColorSegmentation(SegmentationBase):
"""
Perform color segmentation based on a color model or color provided. This class
uses ColorModel.py to create a color model.
"""
mColorModel = []
mError = False
mCurImg = []
mTruthImg = []
mBlobMaker = []
def __init__(self):
self.mColorModel = ColorModel()
self.mError = False
self.mCurImg = Image()
self.mTruthImg = Image()
self.mBlobMaker = BlobMaker()
def addImage(self, img):
"""
Add a single image to the segmentation algorithm
"""
self.mTruthImg = img
self.mCurImg = self.mColorModel.threshold(img)
return
def isReady(self):
"""
Returns true if the camera has a segmented image ready.
"""
return True
def isError(self):
"""
Returns true if the segmentation system has detected an error.
Eventually we'll consruct a syntax of errors so this becomes
more expressive
"""
return self.mError #need to make a generic error checker
def resetError(self):
"""
Clear the previous error.
"""
self.mError = false
return
def reset(self):
"""
Perform a reset of the segmentation systems underlying data.
"""
self.mColorModel.reset()
def getRawImage(self):
"""
Return the segmented image with white representing the foreground
and black the background.
"""
return self.mCurImg
def getSegmentedImage(self, whiteFG=True):
"""
Return the segmented image with white representing the foreground
and black the background.
"""
return self.mCurImg
def getSegmentedBlobs(self):
"""
return the segmented blobs from the fg/bg image
"""
return self.mBlobMaker.extractFromBinary(self.mCurImg, self.mTruthImg)
# The following are class specific methods
def addToModel(self, data):
self.mColorModel.add(data)
def subtractModel(self, data):
self.mColorModel.remove(data)
def __getstate__(self):
mydict = self.__dict__.copy()
self.mBlobMaker = None
del mydict['mBlobMaker']
return mydict
def __setstate__(self, mydict):
self.__dict__ = mydict
self.mBlobMaker = BlobMaker()
def __init__(self):
self.mColorModel = ColorModel()
self.mError = False
self.mCurImg = Image()
self.mTruthImg = Image()
self.mBlobMaker = BlobMaker()
def __init__(self):
self.mColorModel = ColorModel()
self.mError = False
self.mCurImg = Image()
self.mTruthImg = Image()
self.mBlobMaker = BlobMaker()
