Mac/Contrib/ImageHelpers/ImageMac.py - platform/external/python/cpython2 - Gitiles

 '''
 ImageMac.py by Trocca Riccardo (rtrocca@libero.it)
 This module provides functions to display images and Numeric arrays
 It provides two classes ImageMacWin e NumericMacWin and two simple methods showImage and
 showNumeric.

 They work like this:
 showImage(Image,"optional window title",zoomFactor)
 the same for showNumeric
 zoomfactor (defaults to 1) allows to zoom in the image by a factor of 1x 2x 3x and so on
 I did't try with a 0.5x or similar.
 The windows don't provide a scrollbar or a resize box.
 Probably a better solution (and more similar to the original implementation in PIL and NumPy)
 would be to save a temp file is some suitable format and then make an application (through appleevents) to open it.
 Good guesses should be GraphicConverter or PictureViewer.

 However the classes ImageMacWin e NumericMacWin use an extended version of PixMapWrapper in order to
 provide an image buffer and then blit it in the window.

 Being one of my first experiences with Python I didn't use Exceptions to signal error conditions, sorry.

 '''
 import W
 import Qd
 from ExtPixMapWrapper import *
 from Numeric import *
 import Image
 import macfs

 class ImageMacWin(W.Window):

 	def __init__(self,size=(300,300),title="ImageMacWin"):
 		self.pm=ExtPixMapWrapper()
 		self.empty=1
 		self.size=size
 		W.Window.__init__(self,size,title)

 	def Show(self,image,resize=0):
 		#print "format: ", image.format," size: ",image.size," mode: ",image.mode
 		#print "string len :",len(image.tostring())
 		self.pm.fromImage(image)
 		self.empty=0
 		if resize:
 			self.size=(image.size[0]*resize,image.size[1]*resize)
 			W.Window.do_resize(self,self.size[0],self.size[1],self.wid)
 		self.do_drawing()

 	def do_drawing(self):
 		#print "do_drawing"
 		self.SetPort()
 		Qd.RGBForeColor( (0,0,0) )
 		Qd.RGBBackColor((65535, 65535, 65535))
 		Qd.EraseRect((0,0,self.size[0],self.size[1]))
 		if not self.empty:
 			#print "should blit"
 			self.pm.blit(0,0,self.size[0],self.size[1])

 	def do_update(self,macoswindowid,event):
 		#print "update"
 		self.do_drawing()

 class NumericMacWin(W.Window):

 	def __init__(self,size=(300,300),title="ImageMacWin"):
 		self.pm=ExtPixMapWrapper()
 		self.empty=1
 		self.size=size
 		W.Window.__init__(self,size,title)

 	def Show(self,num,resize=0):
 		#print "shape: ", num.shape
 		#print "string len :",len(num.tostring())
 		self.pm.fromNumeric(num)
 		self.empty=0
 		if resize:
 			self.size=(num.shape[1]*resize,num.shape[0]*resize)
 			W.Window.do_resize(self,self.size[0],self.size[1],self.wid)
 		self.do_drawing()

 	def do_drawing(self):
 		#print "do_drawing"
 		self.SetPort()
 		Qd.RGBForeColor( (0,0,0) )
 		Qd.RGBBackColor((65535, 65535, 65535))
 		Qd.EraseRect((0,0,self.size[0],self.size[1]))
 		if not self.empty:
 			#print "should blit"
 			self.pm.blit(0,0,self.size[0],self.size[1])

 	def do_update(self,macoswindowid,event):
 		#print "update"
 		self.do_drawing()

 '''
 Some utilities: convert an Image to a NumPy array and viceversa.
 The Image2Numeric function doesn't make any color space conversion.
 The Numeric2Image function returns an L or RGB or RGBA images depending on the shape of
 the array:
 	(x,y)	-> 	'L'
 	(x,y,1)	-> 	'L'
 	(x,y,3)	->	'RGB'
 	(x,y,4)	->	'RGBA'
 '''
 def Image2Numeric(im):
 	tmp=fromstring(im.tostring(),UnsignedInt8)

 	if (im.mode=='RGB')|(im.mode=='YCbCr'):
 		bands=3

 	if (im.mode=='RGBA')|(im.mode=='CMYK'):
 		bands=4

 	if (im.mode=='L'):
 		bands=1

 	tmp.shape=(im.size[0],im.size[1],bands)
 	return transpose(tmp,(1,0,2))

 def Numeric2Image(num):
 	#sometimes a monoband image's shape can be (x,y,1), other times just (x,y). Here w deal with both
 	if len(num.shape)==3:
 		bands=num.shape[2]
 		if bands==1:
 			mode='L'
 		elif bands==3:
 			mode='RGB'
 		else:
 			mode='RGBA'
 		return Image.fromstring(mode,(num.shape[1],num.shape[0]),transpose(num,(1,0,2)).astype(UnsignedInt8).tostring())
 	else:
 		return Image.fromstring('L',(num.shape[1],num.shape[0]),transpose(num).astype(UnsignedInt8).tostring())

 def showImage(im,title="ImageWin",zoomFactor=1):
 	imw=ImageMacWin((300,200),title)
 	imw.open()
 	try:
 		imw.Show(im,zoomFactor )
 	except MemoryError,e:
 		imw.close()
 		print "ImageMac.showImage: Insufficient Memory"


 def showNumeric(num,title="NumericWin",zoomFactor=1):
 	#im=Numeric2Image(num)
 	numw=NumericMacWin((300,200),title)
 	numw.open()
 	try:
 		numw.Show(num,zoomFactor )
 	except MemoryError:
 		numw.close()
 		print "ImageMac.showNumeric Insufficient Memory"

 '''
 GimmeImage pops up a file dialog and asks for an image file.
 it returns a PIL image.
 Optional argument: a string to be displayed by the dialog.
 '''

 def GimmeImage(prompt="Image File:"):
 	import macfs
 	fsspec, ok = macfs.PromptGetFile(prompt)
 	if ok:
 		path = fsspec.as_pathname()
 		return Image.open(path)
 	return None

 '''
 This is just some experimental stuff:
 	Filter3x3 a convolution filter (too slow use signal tools instead)
 	diffBWImage subtracts 2 images contained in NumPy arrays
 	averageN it computes the average of a list incrementally
 	BWImage converts an RGB or RGBA image (in a NumPy array) to BW
 	SplitBands splits the bands of an Image (inside a NumPy)
 	NumHisto and PlotHisto are some experiments to plot an intesity histogram
 '''

 def Filter3x3(mul,fi,num):
 	(a,b,c,d,e,f,g,h,i)=fi
 	print fi
 	num.shape=(num.shape[0],num.shape[1])
 	res=zeros(num.shape)
 	for x in range(1,num.shape[0]-1):
 		for y in range(1,num.shape[1]-1):
 			xb=x-1
 			xa=x+1
 			yb=y-1
 			ya=y+1
 			res[x,y]=int((a*num[xb,yb]+b*num[x,yb]+c*num[xa,yb]+d*num[xb,y]+e*num[x,y]+f*num[xa,y]+g*num[xb,ya]+h*num[x,ya]+i*num[xa,ya])/mul)
 	return res

 def diffBWImage(num1,num2):
 	return 127+(num1-num2)/2

 def averageN(N,avrg,new):
 	return ((N-1)*avrg+new)/N

 def BWImage(num):
 	if num.shape[2]==3:
 		bw=array(((0.3086,0.6094,0.0820)))
 	else:
 		bw=array(((0.3086,0.6094,0.0820,0)))
 	res=innerproduct(num,bw)
 	res.shape=(res.shape[0],res.shape[1])
 	return res

 def SplitBands(num):
 	x=num.shape[0]
 	y=num.shape[1]
 	if num.shape[2]==3:
 		return (reshape(num[:,:,0],(x,y)),reshape(num[:,:,1],(x,y)),reshape(num[:,:,2],(x,y)))
 	else:
 		return (reshape(num[:,:,0],(x,y)),reshape(num[:,:,1],(x,y)),reshape(num[:,:,2],(x,y)),reshape(num[:,:,3],(x,y)))

 def NumHisto(datas):
 	#print "type(datas) ",type(datas)
 	a=ravel(datas)
 	n=searchsorted(sort(a),arange(0,256))
 	n=concatenate([n,[len(a)]])
 	return n[1:]-n[:-1]

 def PlotHisto(datas,ratio=1):
 	from graphite import *
 	from MLab import max
 	h=NumHisto(datas)
 	#print "histo: ",h
 	#print "histo.shape: ",h.shape
 	maxval=max(h)
 	#print "maxval ",maxval
 	h.shape=(256,1)
 	x=arange(0,256)
 	x.shape=(256,1)
 	datah=concatenate([x,h],1)
 	print "data: "
 	print datah
 	g=Graph()
 	g.datasets.append(Dataset(datah))
 	f0=PointPlot()
 	f0.lineStyle = LineStyle(width=2, color=red, kind=SOLID)
 	g.formats = [f0]
 	g.axes[X].range = [0,255]
 	g.axes[X].tickMarks[0].spacing = 10
 	#g.axes[X].tickMarks[0].labels = "%d"
 	g.axes[Y].range = [0,maxval/ratio]
 	g.bottom = 370
 	g.top =10
 	g.left=10
 	g.right=590

 	genOutput(g,'QD',size=(600,400))

 def test():
 	import MacOS
 	import Image
 	import ImageFilter
 	import Numeric
 	fsspec, ok = macfs.PromptGetFile("Image File:")
 	if ok:
 		path = fsspec.as_pathname()
 		im=Image.open(path)
 		#im2=im.filter(ImageFilter.SMOOTH)
 		showImage(im,"normal")
 		num=Image2Numeric(im)
 		#num=Numeric.transpose(num,(1,0,2))

 		showNumeric(num,"Numeric")

 		print "num.shape ",num.shape
 		showImage(Numeric2Image(num),"difficile")
 		#showImage(im.filter(ImageFilter.SMOOTH),"smooth")
 		#showImage(im.filter(ImageFilter.FIND_EDGES).filter(ImageFilter.SHARPEN),"detail")

 		print "here"
 	else:
 		print "did not open file"

 if __name__ == '__main__':
 	test()
	'''
	ImageMac.py by Trocca Riccardo (rtrocca@libero.it)
	This module provides functions to display images and Numeric arrays
	It provides two classes ImageMacWin e NumericMacWin and two simple methods showImage and
	showNumeric.

	They work like this:
	showImage(Image,"optional window title",zoomFactor)
	the same for showNumeric
	zoomfactor (defaults to 1) allows to zoom in the image by a factor of 1x 2x 3x and so on
	I did't try with a 0.5x or similar.
	The windows don't provide a scrollbar or a resize box.
	Probably a better solution (and more similar to the original implementation in PIL and NumPy)
	would be to save a temp file is some suitable format and then make an application (through appleevents) to open it.
	Good guesses should be GraphicConverter or PictureViewer.

	However the classes ImageMacWin e NumericMacWin use an extended version of PixMapWrapper in order to
	provide an image buffer and then blit it in the window.

	Being one of my first experiences with Python I didn't use Exceptions to signal error conditions, sorry.

	'''
	import W
	import Qd
	from ExtPixMapWrapper import *
	from Numeric import *
	import Image
	import macfs

	class ImageMacWin(W.Window):

	def __init__(self,size=(300,300),title="ImageMacWin"):
	self.pm=ExtPixMapWrapper()
	self.empty=1
	self.size=size
	W.Window.__init__(self,size,title)

	def Show(self,image,resize=0):
	#print "format: ", image.format," size: ",image.size," mode: ",image.mode
	#print "string len :",len(image.tostring())
	self.pm.fromImage(image)
	self.empty=0
	if resize:
	self.size=(image.size[0]resize,image.size[1]resize)
	W.Window.do_resize(self,self.size[0],self.size[1],self.wid)
	self.do_drawing()

	def do_drawing(self):
	#print "do_drawing"
	self.SetPort()
	Qd.RGBForeColor( (0,0,0) )
	Qd.RGBBackColor((65535, 65535, 65535))
	Qd.EraseRect((0,0,self.size[0],self.size[1]))
	if not self.empty:
	#print "should blit"
	self.pm.blit(0,0,self.size[0],self.size[1])

	def do_update(self,macoswindowid,event):
	#print "update"
	self.do_drawing()

	class NumericMacWin(W.Window):

	def __init__(self,size=(300,300),title="ImageMacWin"):
	self.pm=ExtPixMapWrapper()
	self.empty=1
	self.size=size
	W.Window.__init__(self,size,title)

	def Show(self,num,resize=0):
	#print "shape: ", num.shape
	#print "string len :",len(num.tostring())
	self.pm.fromNumeric(num)
	self.empty=0
	if resize:
	self.size=(num.shape[1]resize,num.shape[0]resize)
	W.Window.do_resize(self,self.size[0],self.size[1],self.wid)
	self.do_drawing()

	def do_drawing(self):
	#print "do_drawing"
	self.SetPort()
	Qd.RGBForeColor( (0,0,0) )
	Qd.RGBBackColor((65535, 65535, 65535))
	Qd.EraseRect((0,0,self.size[0],self.size[1]))
	if not self.empty:
	#print "should blit"
	self.pm.blit(0,0,self.size[0],self.size[1])

	def do_update(self,macoswindowid,event):
	#print "update"
	self.do_drawing()

	'''
	Some utilities: convert an Image to a NumPy array and viceversa.
	The Image2Numeric function doesn't make any color space conversion.
	The Numeric2Image function returns an L or RGB or RGBA images depending on the shape of
	the array:
	(x,y) -> 'L'
	(x,y,1) -> 'L'
	(x,y,3) -> 'RGB'
	(x,y,4) -> 'RGBA'
	'''
	def Image2Numeric(im):
	tmp=fromstring(im.tostring(),UnsignedInt8)

	if (im.mode=='RGB')\|(im.mode=='YCbCr'):
	bands=3

	if (im.mode=='RGBA')\|(im.mode=='CMYK'):
	bands=4

	if (im.mode=='L'):
	bands=1

	tmp.shape=(im.size[0],im.size[1],bands)
	return transpose(tmp,(1,0,2))

	def Numeric2Image(num):
	#sometimes a monoband image's shape can be (x,y,1), other times just (x,y). Here w deal with both
	if len(num.shape)==3:
	bands=num.shape[2]
	if bands==1:
	mode='L'
	elif bands==3:
	mode='RGB'
	else:
	mode='RGBA'
	return Image.fromstring(mode,(num.shape[1],num.shape[0]),transpose(num,(1,0,2)).astype(UnsignedInt8).tostring())
	else:
	return Image.fromstring('L',(num.shape[1],num.shape[0]),transpose(num).astype(UnsignedInt8).tostring())

	def showImage(im,title="ImageWin",zoomFactor=1):
	imw=ImageMacWin((300,200),title)
	imw.open()
	try:
	imw.Show(im,zoomFactor )
	except MemoryError,e:
	imw.close()
	print "ImageMac.showImage: Insufficient Memory"


	def showNumeric(num,title="NumericWin",zoomFactor=1):
	#im=Numeric2Image(num)
	numw=NumericMacWin((300,200),title)
	numw.open()
	try:
	numw.Show(num,zoomFactor )
	except MemoryError:
	numw.close()
	print "ImageMac.showNumeric Insufficient Memory"

	'''
	GimmeImage pops up a file dialog and asks for an image file.
	it returns a PIL image.
	Optional argument: a string to be displayed by the dialog.
	'''

	def GimmeImage(prompt="Image File:"):
	import macfs
	fsspec, ok = macfs.PromptGetFile(prompt)
	if ok:
	path = fsspec.as_pathname()
	return Image.open(path)
	return None

	'''
	This is just some experimental stuff:
	Filter3x3 a convolution filter (too slow use signal tools instead)
	diffBWImage subtracts 2 images contained in NumPy arrays
	averageN it computes the average of a list incrementally
	BWImage converts an RGB or RGBA image (in a NumPy array) to BW
	SplitBands splits the bands of an Image (inside a NumPy)
	NumHisto and PlotHisto are some experiments to plot an intesity histogram
	'''

	def Filter3x3(mul,fi,num):
	(a,b,c,d,e,f,g,h,i)=fi
	print fi
	num.shape=(num.shape[0],num.shape[1])
	res=zeros(num.shape)
	for x in range(1,num.shape[0]-1):
	for y in range(1,num.shape[1]-1):
	xb=x-1
	xa=x+1
	yb=y-1
	ya=y+1
	res[x,y]=int((anum[xb,yb]+bnum[x,yb]+cnum[xa,yb]+dnum[xb,y]+enum[x,y]+fnum[xa,y]+gnum[xb,ya]+hnum[x,ya]+i*num[xa,ya])/mul)
	return res

	def diffBWImage(num1,num2):
	return 127+(num1-num2)/2

	def averageN(N,avrg,new):
	return ((N-1)*avrg+new)/N

	def BWImage(num):
	if num.shape[2]==3:
	bw=array(((0.3086,0.6094,0.0820)))
	else:
	bw=array(((0.3086,0.6094,0.0820,0)))
	res=innerproduct(num,bw)
	res.shape=(res.shape[0],res.shape[1])
	return res

	def SplitBands(num):
	x=num.shape[0]
	y=num.shape[1]
	if num.shape[2]==3:
	return (reshape(num[:,:,0],(x,y)),reshape(num[:,:,1],(x,y)),reshape(num[:,:,2],(x,y)))
	else:
	return (reshape(num[:,:,0],(x,y)),reshape(num[:,:,1],(x,y)),reshape(num[:,:,2],(x,y)),reshape(num[:,:,3],(x,y)))

	def NumHisto(datas):
	#print "type(datas) ",type(datas)
	a=ravel(datas)
	n=searchsorted(sort(a),arange(0,256))
	n=concatenate([n,[len(a)]])
	return n[1:]-n[:-1]

	def PlotHisto(datas,ratio=1):
	from graphite import *
	from MLab import max
	h=NumHisto(datas)
	#print "histo: ",h
	#print "histo.shape: ",h.shape
	maxval=max(h)
	#print "maxval ",maxval
	h.shape=(256,1)
	x=arange(0,256)
	x.shape=(256,1)
	datah=concatenate([x,h],1)
	print "data: "
	print datah
	g=Graph()
	g.datasets.append(Dataset(datah))
	f0=PointPlot()
	f0.lineStyle = LineStyle(width=2, color=red, kind=SOLID)
	g.formats = [f0]
	g.axes[X].range = [0,255]
	g.axes[X].tickMarks[0].spacing = 10
	#g.axes[X].tickMarks[0].labels = "%d"
	g.axes[Y].range = [0,maxval/ratio]
	g.bottom = 370
	g.top =10
	g.left=10
	g.right=590

	genOutput(g,'QD',size=(600,400))

	def test():
	import MacOS
	import Image
	import ImageFilter
	import Numeric
	fsspec, ok = macfs.PromptGetFile("Image File:")
	if ok:
	path = fsspec.as_pathname()
	im=Image.open(path)
	#im2=im.filter(ImageFilter.SMOOTH)
	showImage(im,"normal")
	num=Image2Numeric(im)
	#num=Numeric.transpose(num,(1,0,2))

	showNumeric(num,"Numeric")

	print "num.shape ",num.shape
	showImage(Numeric2Image(num),"difficile")
	#showImage(im.filter(ImageFilter.SMOOTH),"smooth")
	#showImage(im.filter(ImageFilter.FIND_EDGES).filter(ImageFilter.SHARPEN),"detail")

	print "here"
	else:
	print "did not open file"

	if __name__ == '__main__':
	test()