Python ImagePlus.show方法代码示例

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def SaveCoverFromFs(tiles, newwidth, newheight, cols, rows):

	tilewidth = int(newwidth/cols)
	tileheight = int(newheight/rows)

	newwidth = int(newwidth/tilewidth) * tilewidth
	newheight = int(newheight/tileheight) * tileheight

	hiresoutip = ColorProcessor(newwidth, newheight)
	hiresout = ImagePlus("hi res output", hiresoutip)
	hiresout.show()

	x = 0
	y = -1

	plane = []

	# scale the images
	for i in sorted(tiles.iterkeys()):
		if y < rows-1:
			y += 1
		else:
			y = 0
			x += 1
		imp = IJ.openImage(str(tiles[i]))
		scale = Scale(imp.getProcessor())
		ipscaled = ScaleImageToSize(scale, tilewidth, tileheight)
		hiresoutip.copyBits(ipscaled, x*tilewidth, y*tileheight, 0)
		hiresout.draw()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def extract_stack_under_arealist():
	# Check that a Display is open
	display = Display.getFront()
	if display is None:
		IJ.log("Open a TrakEM2 Display first!")
		return
	# Check that an AreaList is selected and active:
	ali = display.getActive()
	if ali is None or not isinstance(ali, AreaList):
		IJ.log("Please select an AreaList first!")
		return

	# Get the range of layers to which ali paints:
	ls = display.getLayerSet()
	ifirst = ls.indexOf(ali.getFirstLayer())
	ilast = ls.indexOf(ali.getLastLayer())
	layers = display.getLayerSet().getLayers().subList(ifirst, ilast +1)

	# Create a stack with the dimensions of ali
	bounds = ali.getBoundingBox()
	stack = ImageStack(bounds.width, bounds.height)

	# Using 16-bit. To change to 8-bit, use GRAY8 and ByteProcessor in the two lines below:
	type = ImagePlus.GRAY16
	ref_ip = ShortProcessor(bounds.width, bounds.height)

	for layer in layers:
		area = ali.getArea(layer)
		z = layer.getZ()
		ip = ref_ip.createProcessor(bounds.width, bounds.height)
		if area is None:
			stack.addSlice(str(z), bp)
			continue

		# Create a ROI from the area of ali at layer:
		aff = ali.getAffineTransformCopy()
		aff.translate(-bounds.x, -bounds.y)
		roi = ShapeRoi(area.createTransformedArea(aff))

		# Create a cropped snapshot of the images at layer under ali:
		flat = Patch.makeFlatImage(type, layer, bounds, 1.0, layer.getDisplayables(Patch), Color.black)
		b = roi.getBounds()
		flat.setRoi(roi)
		ip.insert(flat.crop(), b.x, b.y)

		# Clear the outside of ROI (ShapeRoi is a non-rectangular ROI type)
		bimp = ImagePlus("", ip)
		bimp.setRoi(roi)
		ip.setValue(0)
		ip.setBackgroundValue(0)
		IJ.run(bimp, "Clear Outside", "")

		# Accumulate slices
		stack.addSlice(str(z), ip)

	imp = ImagePlus("AreaList stack", stack)
	imp.setCalibration(ls.getCalibrationCopy())
	imp.show()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def draw_bounding_boxes(objects,title,templateImage):
	drawnIp = ByteProcessor(templateImage.getWidth(),templateImage.getHeight())
	drawnImage = ImagePlus(title,drawnIp)
	drawnImage.show()
	IJ.selectWindow(title)
	for j in range(len(objects)):
		IJ.makeRectangle(objects[j][42],objects[j][43],objects[j][45]-objects[j][42],objects[j][46]-objects[j][43])
		IJ.run("Draw","stack")
	drawnImage.hide()
	return(drawnImage)

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def run_script():
    # We can use import inside of code blocks to limit the scope.
    import math
    from ij import IJ, ImagePlus
    from ij.process import FloatProcessor
    blank = IJ.createImage("Blank", "32-bit black", img_size, img_size, 1)
    # This create a list of lists. Each inner list represents a line.
    # pixel_matrix[0] is the first line where y=0.
    pixel_matrix = split_list(blank.getProcessor().getPixels(), wanted_parts=img_size)
    # This swaps x and y coordinates.
    # http://stackoverflow.com/questions/8421337/rotating-a-two-dimensional-array-in-python
    # As zip() creates tuples, we have to convert each one by using list().
    pixel_matrix = [list(x) for x in zip(*pixel_matrix)]
    for y in range(img_size):
        for x in range(img_size):
            # This function oszillates between 0 and 1.
            # The distance of 2 maxima in a row/column is given by spacing.
            val = (0.5 * (math.cos(2*math.pi/spacing*x) + math.sin(2*math.pi/spacing*y)))**2
            # When assigning, we multiply the value by the amplitude.
            pixel_matrix[x][y] = amplitude * val
    # The constructor of FloatProcessor works fine with a 2D Python list.
    crystal = ImagePlus("Crystal", FloatProcessor(pixel_matrix))
    # Crop without selection is used to duplicate an image.
    crystal_with_noise = crystal.crop()
    crystal_with_noise.setTitle("Crystal with noise")
    IJ.run(crystal_with_noise, "Add Specified Noise...", "standard=%d" % int(amplitude/math.sqrt(2)))
    # As this is a demo, we don't want to be ask to save an image on closing it.
    # In Python True and False start with capital letters.
    crystal_with_noise.changes = False
    crystal.show()
    crystal_with_noise.show()
    filtered = fft_filter(crystal_with_noise)
    # We create a lambda function to be used as a parameter of img_calc().
    subtract = lambda values: values[0] - values[1]
    """ This is a short form for:
    def subtract(values):
        return values[0] - values[1]
    """
    # The first time we call img_calc with 2 images.
    difference = img_calc(subtract, crystal, filtered, title="Difference of 2")
    difference.show()
    # The first time we call img_calc with 3 images.
    minimum = img_calc(min, crystal, filtered, crystal_with_noise, title="Minimum of 3")
    minimum.show()
    for imp in (crystal, crystal_with_noise, filtered, difference, minimum):
        IJ.run(imp, "Measure", "")

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def SaveCoverFromZip(tileIndex, newwidth, newheight, cols, rows, originalspath):
	baseDir = re.sub(r'\/originals.zip', "", originalspath)

	#print baseDir

	zf = zipfile.ZipFile(originalspath, mode='r')

	tilewidth = int(newwidth/cols)
	tileheight = int(newheight/rows)

	newwidth = int(newwidth/tilewidth) * tilewidth
	newheight = int(newheight/tileheight) * tileheight

	hiresoutip = ColorProcessor(newwidth, newheight)
	hiresout = ImagePlus("hi res output", hiresoutip)
	hiresout.show()

	x = 0
	y = -1

	plane = []

	# scale the images
	for i in sorted(tileIndex.iterkeys()):
		if y < rows-1:
			y += 1
		else:
			y = 0
			x += 1
		#bi = bir.openImage(tileIndex[i]);
		#ip = ColorProcessor(bi)
		image = zf.read(str(tileIndex[i]) + ".jpeg")
		#IJ.log("Placing image :" + str(tileIndex[i]) + ".jpeg")
		my_file = open(baseDir + 'temporary.jpeg','w')
		my_file.write(image)
		my_file.close()
		imp = IJ.openImage(baseDir + "/temporary.jpeg")
		ip = imp.getProcessor()
		scale = Scale(ip)
		ipscaled = ScaleImageToSize(scale, tilewidth, tileheight)
		hiresoutip.copyBits(ipscaled, x*tilewidth, y*tileheight, 0)
		hiresout.draw()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def run():

    d = str(input_dir)
    files = get_swc_files(d, filenameFilter);
    if not files or len(files) == 0:
        uiservice.showDialog("No files matched the specified criteria", "Error")

    IT = ImportTracings()
    IT.applyScalingFactor(scale_factor, scale_factor, scale_factor)
    # IT.applyCalibration(1, 1, 1, "um")
    proj_rendering = "Projected" in display_choice
    for (counter, f) in enumerate(files):
        basename = os.path.basename(f)
        status.showStatus('Loading file %s: %s...' % (counter + 1, basename))
        try:
            IT.autoLoadSWC(f, proj_rendering)
            if proj_rendering:
                imp = ImagePlus("file: " + basename, IT.getSkeletonizedProjection())
                imp.show()
        except Exception, msg:  # Jython 3: except Exception as msg:
            log.error("An error occurred when loading %s. Details:\n%s" % (f, msg))
            break

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def Extract_Red_Channel(color):
	imp = IJ.getImage()
	stack = imp.getImageStack()  
	print "number of slices:", imp.getNSlices()  
	# A list of red slices  
	reds = []  
	# Iterate each slice in the stack  
	for i in xrange(1, imp.getNSlices()+1):  
	  # Get the ColorProcessor slice at index i  
	  cp = stack.getProcessor(i)  
	  # Get its green channel as a FloatProcessor  
	  fp = cp.toFloat(0, None)  
	  # ... and store it in a list  
	  reds.append(fp)  
	# Create a new stack with only the green channel  
	stack2 = ImageStack(imp.width, imp.height)  
	for fp in reds:  
	  stack2.addSlice(None, fp)  
	# Create a new image with the stack of green channel slices  
	imp2 = ImagePlus("Red channel", stack2)  
	# Set a green look-up table:  
	IJ.run(imp2, "Red", "")  
	imp2.show()  	

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
  lRound  = rt.getColumn(rt.getColumnIndex("Round"))
  lSolid  = rt.getColumn(rt.getColumnIndex("Solidity"))
  for j in range(len(lArea)):
    imgOut.append(iNum)
    parOut.append(j+1)
    ecd = 2.0*sqrt(lArea[j]/3.1415926)
    ecdOut.append(ecd)
    con = 1.0-(lMode[j]/iZero)
    conOut.append(con)   
    cirOut.append(lCirc[j])
    arOut.append(lAspRat[j])
    rndOut.append(lRound[j])
    solOut.append(lSolid[j])
    
    
  orig.show()
  outPth = sRptImgPath + strName + ".png"
  # burn a scale bar and save the image
  IJ.run(orig, "RGB Color", "")
  IJ.run(orig, "Add Scale Bar", strBar)
  IJ.saveAs(orig, "PNG", outPth)
  orig.changes = False
  orig.close()

  print("%d particles detected in image %s" % (nMeas, strNum))

# prepare the output file
f=open(sRptCsvPath, 'w')
strLine = 'img, part, ecd.nm, contrast, circ, a.r, round, solidity\n'
f.write(strLine)
for k in range(len(ecdOut)):

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
	in_f = 0
	avt = 1
	for jj in range(imp.height):
		for ii in range(imp.width):
			if pix_new_green[k] != 0:
				in_f = 1

		if in_f == 1 :
			avt = 1
		
		if in_f == 0 & avt == 1:
			print jj
			avt = 0
		
		in_f = 0
	
	cp = slice.duplicate()
	cp.setPixels(0, new_red)   # at channel 0, the red
	new_stack.addSlice(stack.getSliceLabel(i), cp)
	cp.setPixels(1, new_green)   # at channel 0, the red
	new_stack.addSlice(stack.getSliceLabel(i), cp)
	cp.setPixels(2, new_blue)   # at channel 0, the red
	new_stack.addSlice(stack.getSliceLabel(i), cp)

	new_imp = ImagePlus("g-r subtracted", new_stack)
	new_imp.show()


		

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
# Straighten: like the command in Edit > Selection menu, 
# this snippet creates a new image by taking some pixels along a
# line ROI. It is typically used to make a straight image from
# a bent selection.
from ij import IJ, ImagePlus
width = 20 # how many pixels should we fetch from around the ROI?
# Get current ImagePlus
image = IJ.getImage()
if image is not None:
  roi = image.getRoi()
  if roi is not None and roi.isLine(): # we can only do it for line ROIs
    # Instantiate plugin
    straightener = Straightener()
    # Are we dealing with a stack?
    stack_size = image.getStackSize()
    if stack_size > 1:
      new_stack = straightener.straightenStack(image, roi, width)
      new_image = ImagePlus( image.getTitle()+"-straightened", new_stack)
    else:
      new_ip = straightener.straighten(image, roi, width)
      new_image = ImagePlus( image.getTitle()+"-straightened", new_ip)
    # Display result
    new_image.show()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
from ij import IJ, ImagePlus


orig = IJ.getImage()
cal = orig.getCalibration()
inf = orig.getProperty("Info")
new = orig.duplicate()
ti = orig.getShortTitle()
IJ.run(new, "32-bit", "")
new.setTitle(ti + "-32")
ip = new.getProcessor()

minV = ip.getMin()
maxV = ip.getMax()
delta = maxV-minV
factor = 1.0/delta

pixels = ip.getPixels()
for i in xrange(len(pixels)):  
  pixels[i] -= minV
  pixels[i] *= factor

new = ImagePlus(ti + "-32", ip)  
new.setDisplayRange(0.0, 1.0)
new.setCalibration(cal)
new.setProperty("Info", inf)

# print(minV, maxV)

new.show()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
def processOneImage(inputDir):
    tmp = glob.glob(os.path.join(inputDir, "fibrone*"))
    fibronectin = tmp[0]
    tmp = glob.glob(os.path.join(inputDir, "nucleus*"))
    nucleus = tmp[0]
    tmp = glob.glob(os.path.join(inputDir, "actin*"))
    actin = tmp[0]
    
    # read sample name
    head,tail = os.path.split(inputDir)
    sample = tail.replace(".tif_Files","")

    # original images
    imp_fn_orig = IJ.openImage(fibronectin)
    imp_nuc_orig = IJ.openImage(nucleus)

    # work copies
    imp_fn = imp_fn_orig.duplicate()
    imp_nuc = imp_nuc_orig.duplicate()

    IJ.run(imp_fn,"Set Scale...", "distance=1 known=1 pixel=1 unit=pixels")
    IJ.run(imp_fn,"Gaussian Blur...","sigma=5")
    IJ.run(imp_fn,"Make Binary","")
    IJ.run(imp_nuc,"Set Scale...", "distance=1 known=1 pixel=1 unit=pixels")
    IJ.run(imp_nuc,"Gaussian Blur...","sigma=5")
    IJ.run(imp_nuc,"Make Binary","")

    # get moments of the fibronectin image
    moments_file = os.path.join(OUTPUT, sample + " moments.txt")
    printMoments(fibronectin, moments_file)
    moments = readMoments(moments_file)
    print moments.m00
    sys.exit()

    # centroid of fibronectin anchor
    centers = getParticleCenters(imp_fn)
    cxfn = int(round(centers[0][0]))
    cyfn = int(round(centers[1][0]))
    fn_centroid_roi = PointRoi(cxfn,cyfn)
    fn_centroid_roi.setDefaultMarkerSize("Large")
    fn_centroid_roi.setStrokeColor(Color.CYAN)

    # center of mass of nucleus 
    centers = getParticleCenters(imp_nuc)
    cxnuc = int(round(centers[2][0]))
    cynuc = int(round(centers[3][0]))
    nuc_com_roi = PointRoi(cxnuc,cynuc)
    nuc_com_roi.setDefaultMarkerSize("Large")

    # skeletonize fibronectin anchor to find its orientation
    IJ.run(imp_fn,"Skeletonize","")
    skel = AnalyzeSkeleton_()
    skel.setup("",imp_fn)
    skelResult = skel.run(skel.NONE, False, True, None, True, True)
    graph = skelResult.getGraph()
    print len(graph)
    print skelResult.getNumOfTrees()
    # find the longest graph
    graph = sorted(graph, key=lambda g: getGraphLength(g), reverse=True)
    graph = graph[0]
    edges = graph.getEdges()
    # find longest edge, the main axis of the anchor
    edges = sorted(edges, key=lambda edge: edge.getLength(), reverse=True)
    #for e in edges:
    #    print e.getLength()
    v1long = edges[0].getV1()
    v2long = edges[0].getV2()
    x1 = v1long.getPoints()[0].x
    y1 = v1long.getPoints()[0].y
    x2 = v2long.getPoints()[0].x
    y2 = v2long.getPoints()[0].y
    anchor_roi = PointRoi(x1,y1)
    anchor_roi = anchor_roi.addPoint(x2,y2)
    # find top and bottom vertices of the graph
    vertices = graph.getVertices()
    vertices = sorted(vertices, key=lambda vertex: vertex.getPoints()[0].y)
    v1short = vertices[len(vertices)-1]
    v2short = vertices[0]
    x3 = v1short.getPoints()[0].x
    y3 = v1short.getPoints()[0].y
    x4 = v2short.getPoints()[0].x
    y4 = v2short.getPoints()[0].y
    anchor_roi = anchor_roi.addPoint(x3,y3)
    anchor_roi = anchor_roi.addPoint(x4,y4)
    # calculate angles
    a1 = math.atan(abs(float(y2-y1)/float(x2-x1))) / math.pi * 360
    a2 = math.atan(abs(float(x4-x3)/float(y4-y3))) / math.pi * 360
    amean = float((a1+a2)/2)
    dx = cxfn-cxnuc
    print sample,cxfn,cyfn,cxnuc,cynuc,dx,math.cos(amean)*dx,x1,y1,x2,y2,x3,y3,x4,y4,a1,a2

    # create composite
    comp = ImagePlus("composite",imp_nuc_orig.getProcessor().convertToColorProcessor())
    comp.getProcessor().setChannel(2,imp_fn_orig.getProcessor())
    comp.getProcessor().setChannel(3,imp_fn.getProcessor())
    comp.show()
    comp.getProcessor().drawRoi(fn_centroid_roi)
    comp.getProcessor().drawRoi(nuc_com_roi)
    comp.getProcessor().drawRoi(anchor_roi)
    comp.repaintWindow()
#.........这里部分代码省略.........

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
impG = WindowManager.getImage(imgNamG)
impG.show()

# create a gray image fo redirect...
impGbare = impG.duplicate()
impGbare.setTitle("green_channel")
impGbare.show()

impG.setRoi(OvalRoi(22,12,334,337))
impG.show()

w = impG.getWidth()
h = impG.getHeight()
print(w, h)
sp = ByteProcessor(w,h)
blank = ImagePlus("blank", sp)
pix = blank.getProcessor().getPixels()
for i in range(len(pix)):
   pix[i] = -1

blank.show()

IJ.selectWindow("original (green)");
IJ.run("Copy")
IJ.selectWindow("blank")
IJ.run("Paste")

blank.show()

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
	def makeMask(self):
		"""
		This function makes the mask. The steps are (1) Minimum Filter - makes a darker boundary around beads (2) Autothresholding using the Huang algorithm - has some fuzzy logic and seems to work (3) Analyze particles with a size between 500-50000 and 
		circularity between 0.4 to 1.0; The mask generated is sometimes black on beads and white around. Then I need to invert the LUTs
		"""
	
		ipOriginal = self.stack.getProcessor(self.DIC_index)
		ip = ipOriginal.duplicate()
		imgUpdate = ImagePlus("New",ip)
		imgUpdate.setProcessor("Mask",ip)
		
		img0 = ImagePlus("Before",ipOriginal)
		img0.show()
		
		# Minimum filter
		RankFilters().rank(ip,2,RankFilters.MIN)
		img1 = ImagePlus("Filter",ip)
		# Autothreshold - Huang algorithm
		hist = ip.getHistogram()
		lowTH = Auto_Threshold.Huang(hist)
		ip.setThreshold(0,lowTH, ImageProcessor.BLACK_AND_WHITE_LUT)
		img3 = ImagePlus("Thresholded",ip)
		img3.show()

		# Making a binary mask
		IJ.run(img3,"Convert to Mask","")
		
		if self._dialog("Invert Mask ??") is True: IJ.run("Invert LUT")
		img3.updateAndDraw()
		
		# The true mask after Particle Analysis; Creates a mask image around the particles
		IJ.run(img3,"Analyze Particles...", "size=500-50000 circularity=0.40-1.00 show=Masks")
		img1.close()
		#img3.close()

		# Editing the masks (filling holes and dilating it twice)
		imgActive = IJ.getImage()
		IJ.run(imgActive,"Convert to Mask","")
		IJ.run(imgActive,"Fill Holes","")
		for i in range(8): IJ.run(imgActive,"Dilate","")
		ipActive = imgActive.getProcessor().convertToFloat()
		
		# Saving the mask
		maskFname = self.sourceDir + "\\" + self.title + '_mask'
		IJ.saveAs(imgActive, "PNG", maskFname)
				
		# Confirming that the image is masked and the histogram is correct
		#IJ.run(imgActive, "Histogram", "")
		
		#stats = ipActive.getStatistics()
		pixels = ipActive.getPixels()
		self.maskPixels = [pix/255 for pix in pixels]
		self.areaMask = self.maskPixels.count(1)

		# Checking if the image is fine. If not, returns option to skip
		ImageCalculator().calculate("zero create", img0, imgActive)

		skip = False
		if self._dialog("Skip Image ??") is True: skip = True

		IJ.run("Close All")
		return self.maskPixels, skip

# 需要导入模块: from ij import ImagePlus [as 别名]
# 或者: from ij.ImagePlus import show [as 别名]
 def openImp(self, path):
    imp = ImagePlus(path)  # open associated tif file
    imp.show()
    imp.getWindow().setLocationAndSize(280, 120, imp.getWidth()*4, imp.getHeight()*4) # int x, int y, int width, int height
    return imp