def getTransitions(self, frm):
tos = iulib.intarray()
symbols = iulib.intarray()
costs = iulib.floatarray()
inputs = iulib.intarray()
self.comp.getTransitions(tos, symbols, costs, inputs, frm)
return (iulib.numpy(tos, 'i'), iulib.numpy(symbols, 'i'),
iulib.numpy(costs), iulib.numpy(inputs, 'i'))
def beam_search(lattice, lmodel, beam):
"""Perform a beam search through the lattice and language model, given the
beam size. Returns (v1,v2,input_symbols,output_symbols,costs)."""
v1 = iulib.intarray()
v2 = iulib.intarray()
ins = iulib.intarray()
outs = iulib.intarray()
costs = iulib.floatarray()
ocrofstll.beam_search(v1, v2, ins, outs, costs, native_fst(lattice),
native_fst(lmodel), beam)
return (iulib.numpy(v1, 'i'), iulib.numpy(v2, 'i'), iulib.numpy(ins, 'i'),
iulib.numpy(outs, 'i'), iulib.numpy(costs, 'f'))
def narray2numpy(na,type='B'):
"""Convert an narray image to a numpy image. Flips from mathematical
coordinates to raster coordinates. When converting integer to float
types, multiplies with 255.0, and when converting integer to float
types divides by 255.0"""
checkna(na)
if type is None: type = ctype(na)
if isfp(na) and not isfp(type):
page = iulib.numpy(na,'f')
page = array(255.0*page,dtype=type)
elif not isfp(na) and isfp(type):
page = iulib.numpy(na,type=type)
page /= 255.0
else:
page = iulib.numpy(na,type=type)
return page.transpose([1,0]+range(2,page.ndim))[::-1,...]
def narray2lseg(na):
"""Convert an narray to a line segmentation."""
checkna(na)
pseg = iulib.numpy(na, type='i')
pseg = transpose(pseg, [1, 0])
pseg = pseg[::-1, ...]
return pseg
def narray2lseg(na):
"""Convert an narray to a line segmentation."""
checkna(na)
pseg = iulib.numpy(na,type='i')
pseg = transpose(pseg,[1,0])
pseg = pseg[::-1,...]
return pseg
def narray2numpy(na, type='B'):
"""Convert an narray image to a numpy image. Flips from mathematical
coordinates to raster coordinates. When converting integer to float
types, multiplies with 255.0, and when converting integer to float
types divides by 255.0"""
checkna(na)
if type is None: type = ctype(na)
if isfp(na) and not isfp(type):
page = iulib.numpy(na, 'f')
page = array(255.0 * page, dtype=type)
elif not isfp(na) and isfp(type):
page = iulib.numpy(na, type=type)
page /= 255.0
else:
page = iulib.numpy(na, type=type)
return page.transpose([1, 0] + range(2, page.ndim))[::-1, ...]
def narray2pseg(na):
"""Convert an narray to a page segmentation (rank 3, RGB)."""
checkna(na)
pseg = iulib.numpy(na,type='i')
pseg = array([pseg>>16,pseg>>8,pseg],'B')
pseg = transpose(pseg,[2,1,0])
pseg = pseg[::-1,...]
return pseg
def narray2pseg(na):
"""Convert an narray to a page segmentation (rank 3, RGB)."""
checkna(na)
pseg = iulib.numpy(na, type='i')
pseg = array([pseg >> 16, pseg >> 8, pseg], 'B')
pseg = transpose(pseg, [2, 1, 0])
pseg = pseg[::-1, ...]
return pseg
def show_segmentation(rseg):
"""Shows a line or page segmentation using Matplotlib's imshow.
The argument should be an narray."""
temp = iulib.numpy(rseg, type='B')
temp[temp == 255] = 0
temp = transpose(temp)[::-1, :]
temp2 = 1 + (temp % 10)
temp2[temp == 0] = 0
temp = temp2
print temp.shape, temp.dtype
temp = temp / float(amax(temp))
imshow(temp, cmap=cm.spectral)
def N(image):
"""Convert an iulib array to a numpy image."""
return iulib.numpy(image)
def narray2vector(na,type='f'):
"""Convert an narray vector to numpy. If ndim>1, it converts to
raster coordinates. This is used with classifiers."""
a = iulib.numpy(na)
if a.ndim>1: return a.transpose([1,0]+range(2,a.ndim))[::-1,...]
else: return a
def numpy(self):
"""Convert an narray to a numpy array."""
return iulib.numpy(self)
def narray2vector(na, type='f'):
"""Convert an narray vector to numpy. If ndim>1, it converts to
raster coordinates. This is used with classifiers."""
a = iulib.numpy(na)
if a.ndim > 1: return a.transpose([1, 0] + range(2, a.ndim))[::-1, ...]
else: return a
def as_numpyI(image, dtype=dtype):
if type(image) == numpy.ndarray: return image
image = iulib.numpy(image, type=dtype)
image = image.transpose([1, 0] + range(2, image.ndim))
return image[::-1, ...]
def N(image):
"""Convert an narray to a numpy array."""
return iulib.numpy(image)
def as_numpy(image, flip=0, dtype='f'):
if type(image) == numpy.ndarray: return image
if flip and image.rank() > 1: return as_numpyI(image, dtype=dtype)
return iulib.numpy(image, type=dtype)
