def __init__(self,size,use_previous=0,blocksize=(8,8),shiftsize=(8,8),maxrange=(8,8),bfc=0):
self.use_previous=use_previous
self.blocksize=zcv.cvSize(blocksize[0],blocksize[1])
self.shiftsize=zcv.cvSize(shiftsize[0],shiftsize[1])
self.maxrange=zcv.cvSize(maxrange[0],maxrange[1])
self.imgprev=None
self.imgvelx=numpy.ndarray(shape=((size[0]-bfc*blocksize[1])//shiftsize[1],(size[1]-bfc*blocksize[0])//shiftsize[0]),dtype=numpy.float32)
self.cvimgvelx=zcv.NumPy2CvMatFast(self.imgvelx)
self.imgvely=numpy.ndarray(shape=((size[0]-bfc*blocksize[1])//shiftsize[1],(size[1]-bfc*blocksize[0])//shiftsize[0]),dtype=numpy.float32)
self.cvimgvely=zcv.NumPy2CvMatFast(self.imgvely)
def PIL2zIpl(input):
"""Converts a PIL image to the OpenCV/IPL CvMat data format.
Supported input image formats are:
RGB
L
F
"""
if not (isinstance(input, PIL.Image.Image) or isinstance(input, Image.Image)):
raise TypeError, 'Must be called with PIL.Image.Image or Image.Image!'
# mode dictionary:
# (pil_mode : (ipl_depth, ipl_channels)
mode_list = {
"RGB" : (zcv.IPL_DEPTH_8U, 3),
"L" : (zcv.IPL_DEPTH_8U, 1),
"F" : (zcv.IPL_DEPTH_32F, 1)
}
if not mode_list.has_key(input.mode):
raise ValueError, 'unknown or unsupported input mode'
result = zcv.cvCreateImage(
zcv.cvSize(input.size[0], input.size[1]), # size
mode_list[input.mode][0], # depth
mode_list[input.mode][1] # channels
)
# set imageData
result.imageData = input.tostring()
return result
def __init__(self,size,use_previous=0,winsize=(7,7)):
self.use_previous=use_previous
self.winsize=zcv.cvSize(winsize[0],winsize[1])
self.imgprev=None
self.imgvelx=numpy.ndarray(shape=(size[0],size[1]),dtype=numpy.float32)
self.cvimgvelx=zcv.NumPy2CvMatFast(self.imgvelx)
self.imgvely=numpy.ndarray(shape=(size[0],size[1]),dtype=numpy.float32)
self.cvimgvely=zcv.NumPy2CvMatFast(self.imgvely)
def NumPy2zIplFastWithCopy(input):
mode_list = {
numpy.dtype(numpy.uint8) : zcv.IPL_DEPTH_8U,
numpy.dtype(numpy.uint16) : zcv.IPL_DEPTH_16U,
numpy.dtype(numpy.int8) : zcv.IPL_DEPTH_8S,
numpy.dtype(numpy.int16) : zcv.IPL_DEPTH_16S,
numpy.dtype(numpy.int32) : zcv.IPL_DEPTH_32S,
numpy.dtype(numpy.float32) : zcv.IPL_DEPTH_32F,
numpy.dtype(numpy.float64) : zcv.IPL_DEPTH_64F,
}
if not mode_list.has_key(input.dtype):
raise ValueError, 'unknown or unsupported input mode'
result = zcv.cvCreateImage(zcv.cvSize(input.shape[1], input.shape[0]), # size
mode_list[input.dtype], # depth
input.shape[2]
)
result.imageData = input.tostring()
return result
def snake(src,alpha=0.45,beta=0.2,gamma=0.45,max_iter=1000,epsilon=0.001,length=int(50),neigborhoodsize=(10,10)):
CV_VALUE=1
if (src.ndim==2):
src=src.reshape(src.shape+(1,))
if (src.shape[2]!=1):
src=src.mean(axis=2)
src=src.astype(numpy.uint8)
w2,h2=src.shape[1]/2,src.shape[0]/2
points=(numpy.vstack([scipy.cos(numpy.arange(0,scipy.pi*2,scipy.pi*2./length))*w2+w2,scipy.sin(numpy.arange(0,scipy.pi*2,scipy.pi*2./length))*h2+h2])).T.astype(numpy.int32)
alpha=numpy.array([alpha], dtype=numpy.float32)
beta=numpy.array([beta], dtype=numpy.float32)
gamma=numpy.array([gamma], dtype=numpy.float32)
size=zopencv.cvSize(neigborhoodsize[0]|1,neigborhoodsize[1]|1)
criteria=zopencv.CvTermCriteria()
criteria.type=zopencv.CV_TERMCRIT_ITER+zopencv.CV_TERMCRIT_EPS;
criteria.max_iter=max_iter;
criteria.epsilon=epsilon;
zopencv.cvSnakeImage( src, zopencv.memory_addr_of_numpy_array(points),length,alpha,beta, gamma,CV_VALUE,size,criteria,0 );
return points
