def update_image(self):
"""
generates the PIL Image representation of this numpy array
"""
clip = self.transform['clip']
final = imagefun.linearscale(self.orig_array, clip, (0, 255),
self.extrema)
type = final.dtype
h, w = final.shape
imsize = w, h
itemsize = final.itemsize
immode = ntype_itype[type.type, itemsize][0]
rawmode = ntype_itype[type.type, itemsize][1]
nstr = final.tostring()
stride = 0
orientation = 1
image = Image.fromstring(immode, imsize, nstr, 'raw', rawmode, stride,
orientation)
image = resize(image, self.transform['output_size'])
self.image = image
return self.image
def numpy2PILImage(numericarray, scale=False): if scale: numericarray = imagefun.linearscale(numericarray, (None, None), (0, 255)).astype(numpy.uint8) type = numericarray.dtype h, w = numericarray.shape imsize = w, h itemsize = numericarray.itemsize() immode = ntype_itype[type.type, itemsize][0] rawmode = ntype_itype[type.type, itemsize][1] nstr = numericarray.tostring() return Image.fromstring(immode, imsize, nstr, 'raw', rawmode, 0, 1)
def numpy2PILImage(numericarray, scale=False):
if scale:
numericarray = imagefun.linearscale(numericarray, (None, None),
(0, 255)).astype(numpy.uint8)
type = numericarray.dtype
h, w = numericarray.shape
imsize = w, h
itemsize = numericarray.itemsize()
immode = ntype_itype[type.type, itemsize][0]
rawmode = ntype_itype[type.type, itemsize][1]
nstr = numericarray.tostring()
return Image.fromstring(immode, imsize, nstr, 'raw', rawmode, 0, 1)
def update_image(self): """ generates the PIL Image representation of this numpy array """ clip = self.transform['clip'] final = imagefun.linearscale(self.orig_array, clip, (0,255), self.extrema) type = final.dtype h,w = final.shape imsize = w,h itemsize = final.itemsize immode = ntype_itype[type.type,itemsize][0] rawmode = ntype_itype[type.type,itemsize][1] nstr = final.tostring() stride = 0 orientation = 1 image = Image.fromstring(immode, imsize, nstr, 'raw', rawmode, stride, orientation) image = resize(image, self.transform['output_size']) self.image = image return self.image
quality=quality)
def read_jpeg(self, filename):
'''
read a grey JPEG
'''
i = Image.open(filename)
i.load()
s = i.tostring()
n = numpy.fromstring(s, '1')
n.shape = i.size
self.__use_numeric(n)
if __name__ == '__main__':
from numpy import *
a = array([5, 6, 7, 8, 9], Float)
print 'a', a
b = imagefun.linearscale(a, (None, None), (0, 1))
print 'b', b
b = imagefun.linearscale(a, (6, 8), (0, 1))
print 'b', b
b = imagefun.linearscale(a, (8, 6), (0, 1))
print 'b', b
b = imagefun.linearscale(a, (6, 8), (1.0, -1.0))
print 'b', b
#a1 = reshape(arrayrange(128**2), (128,128))
#n1 = NumericImage(a)
else:
img.convert('L').resize(newsize).save(filename, "JPEG", quality=quality)
def read_jpeg(self, filename):
'''
read a grey JPEG
'''
i = Image.open(filename)
i.load()
s = i.tostring()
n = numpy.fromstring(s, '1')
n.shape = i.size
self.__use_numeric(n)
if __name__ == '__main__':
from numpy import *
a = array([5,6,7,8,9], Float)
print 'a', a
b = imagefun.linearscale(a, (None,None), (0,1))
print 'b', b
b = imagefun.linearscale(a, (6,8), (0,1))
print 'b', b
b = imagefun.linearscale(a, (8,6), (0,1))
print 'b', b
b = imagefun.linearscale(a, (6,8), (1.0,-1.0))
print 'b', b
#a1 = reshape(arrayrange(128**2), (128,128))
#n1 = NumericImage(a)
