cpython/Mac/Contrib/ImageHelpers/ImageMac.py

277 lines
7.4 KiB
Python

'''
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()