Live difference
Python Script
Code to process the live-view image in DigitalMicrograph, producing a difference image. Two exponentially weighted moving averages are computed, and the absolute value of the difference between them is returned.
Preview
'''
Code to process the live-view image in GMS, producing a difference image
Two exponentially weighted moving averages are computed, and
the absolute value of the difference between them returned.
WARNING: Due to a bug in GMS 3.5.0 and 3.5.1, this script will not run in those versions
Run the code with the live-view image, containing a rectangular ROI, front-most in GMS
The code also works with an IS video played back with the IS player
To stop calculation, delete the ROI.
New frames are computed as often as possible.
Lines of code between #XXXXXXXX... lines can be changed to add processing
All other lines of code are general, and can be re-used to produce other kinds of processed images from a live-view image
#Code written by Ben Miller. Last Updated Apr 2022
'''
import time
import numpy as np
import traceback
if not DM.IsScriptOnMainThread(): print('Scipy scripts cannot be run on Background Thread.'); exit()
import scipy.ndimage.filters as sfilt
#User editable variables are set here
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Moving_Avg_Period_1 = 5 # (Default 5) Period (# frames) for first exponentially weighted moving average
Moving_Avg_Period_2 = 10 # (Default 5) Period (# frames) for first exponentially weighted moving average
Filter_Data_First = True # (Default True) Select whether to filter data first with a gaussian blur filter
print_timing = True # (Default True) Select whether to output the time it takes to compute each frame
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
class CListen(DM.Py_ScriptObject):
#Function to find an ROI placed on an image by the user, returning the ROI ID.
#If no ROI found, create a new one covering the entire image.
def find_ROI(self,image):
imageDisplay = image.GetImageDisplay(0)
numROIs = imageDisplay.CountROIs()
id = None
for n in range(numROIs):
roi = imageDisplay.GetROI(n)
if roi.IsRectangle():
roi.SetVolatile(False)
roi.SetResizable(False)
id = roi.GetID()
break
if id is None:
#If No ROI is found, create one that covers the whole image.
print("\nRectangular ROI not found... using whole image")
data_shape = image.GetNumArray().shape
roi=DM.NewROI()
roi.SetRectangle(0, 0, data_shape[0], data_shape[1])
imageDisplay.AddROI(roi)
roi.SetVolatile(False)
roi.SetResizable(False)
id = roi.GetID()
return id
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
def exp_moving_avg(self, img_frame, old_avg, frames_to_sum=5):
persistence = (frames_to_sum-1)/(frames_to_sum+1)
old_avg = persistence*old_avg.astype('float32') + (1-persistence)*img_frame.astype('float32')
return(old_avg)
def ROI_process(self,image_data):
if Filter_Data_First: image_data = sfilt.gaussian_filter(image_data, 2)
self.old_avg1 = self.exp_moving_avg(image_data, self.old_avg1, frames_to_sum=Moving_Avg_Period_1)
self.old_avg2 = self.exp_moving_avg(image_data, self.old_avg2, frames_to_sum=Moving_Avg_Period_2)
return np.abs(self.old_avg2-self.old_avg1)
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
#Initialization Function
def __init__(self,img):
try:
#Create an index that is incremented each time data is processed.
self.i = 0
#get the original image and assign it to self.imgref
self.imgref = img
#Get the data from the region within an ROI
self.roi = DM.GetROIFromID(self.find_ROI(self.imgref))
val, val2, val3, val4 = self.roi.GetRectangle()
self.data = self.imgref.GetNumArray()[int(val):int(val3),int(val2):int(val4)]
#get the shape and calibration of the original image
(input_sizex, input_sizey) = self.data.shape
x_origin = self.imgref.GetDimensionOrigin(0); y_origin = self.imgref.GetDimensionOrigin(1)
x_scale = self.imgref.GetDimensionScale(0); y_scale = self.imgref.GetDimensionScale(1)
#scale unit of microns causes problems for python in DM
try:
x_unit = self.imgref.GetDimensionUnitString(0) ; y_unit = self.imgref.GetDimensionUnitString(1)
except:
x_unit = self.imgref.GetDimensionUnitInfo(0)[0]; y_unit = self.imgref.GetDimensionUnitInfo(1)[0]
if x_unit == 'micrometer': x_unit = 'um'
if y_unit == 'micrometer': y_unit = 'um'
#Initialize Data for running averages
self.old_avg1 = self.data
self.old_avg2 = self.data
#Create a new image to contain the results of processing
self.result_image = DM.CreateImage(self.ROI_process(self.data))
#Set the calibration based on the original data
self.result_image.SetDimensionCalibration(0,x_origin,x_scale,x_unit,0)
self.result_image.SetDimensionCalibration(1,y_origin,y_scale,y_unit,0)
#Copy tags from original to processed image
Tag_Copy(self.imgref, self.result_image)
#Get the numpy array of the result image so I can directly change the data values later
self.result_data=self.result_image.GetNumArray()
#Display the result image in GMS
self.result_image.ShowImage()
#Initialize Data for running averages
self.prev_frame = self.result_data
#Set the image name which will be displayed in the image window's title bar
self.result_image.SetName("Exp Moving Difference of "+img.GetName())
DM.Py_ScriptObject.__init__(self)
self.stop = 0
except: print(traceback.format_exc())
#This function is run each time the image changes
def HandleDataChangedEvent(self, flags, image):
try:
if not self.stop:
#start timing
start=time.perf_counter()
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
#Get an (updated) ROI position
val, val2, val3, val4 = self.roi.GetRectangle()
#Get the data from the ROI area as a numpy array
self.data = self.imgref.GetNumArray()[int(val):int(val3),int(val2):int(val4)]
#Process the data and place in the result array (note that the [:] here is essential)
self.result_data[:]=self.ROI_process(self.data)
#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
#Update the result image display
self.result_image.UpdateImage()
#end timing and output time to process this frame
end=time.perf_counter()
if print_timing: print("Processed Image "+str(self.i)+" Processing Time= "+str(end-start))
#Increment an index each time data is processed.
self.i = self.i+1
except: print(traceback.format_exc())
#Function to Delete Image Listener
def __del__(self):
print("Listener Deleted")
DM.Py_ScriptObject.__del__(self)
#Function to end processing by deleting or unregistering listener
def RemoveListeners(self):
try:
if not self.stop:
self.stop = 1
DM.DoEvents()
global listener
#DM 3.5.2 and higher have new function for unregistering listeners.
#DM 3.4.3 and lower should delete the listener instead
#DM 3.5.0 and 3.5.1 have a fatal flaw regarding listeners, so this script is not compatible with those versions
if (get_DM_version()[1][0] == "4" and get_DM_version()[0] == "3"):
del listener
else:
listener.UnregisterAllListeners()
print("Live Processing Script Ended")
except: print(traceback.format_exc())
#Remove listeners if source image window is closed
def HandleWindowClosedEvent(self, event_flags, window):
print("Window Closed")
self.RemoveListeners()
#Remove listeners if the ROI is deleted
def HandleROIRemovedEvent(self, img_disp_event_flags, img_disp, roi_change_flag, roi_disp_change_flags, roi):
print("ROI Removed")
self.RemoveListeners()
#Function to get the currently used version of DigitalMicrograph
def get_DM_version():
#No Python script command exists to get the DM version,
#so we first run a DM script to put the values in the global tags
dm_script = ('number minor, major, bugVersion\n'
'GetApplicationVersion(major, minor, bugVersion)\n'
'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_Major",major)\n'
'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_Minor",minor)\n'
'GetPersistentTagGroup().TagGroupSetTagAsLong("Python_Temp:DM_Version_bugVersion",bugVersion)')
DM.ExecuteScriptString(dm_script)
#Now get the information stored in the global tags by the DM script
version = [0,0,0]
_,version[0] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_Major")
_,version[1] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_Minor")
_,version[2] = DM.GetPersistentTagGroup().GetTagAsString("Python_Temp:DM_Version_bugVersion")
return version
def Tag_Copy(image_source, image_dest, subPath = None ):
'''
Copy all tags between source and destination.
If no destination subPath is provided, the destination tags will be replaced.
'''
#Copy Tags
tg_source = image_source.GetTagGroup()
tg_dest = image_dest.GetTagGroup()
if ( subPath != None ):
tg_dest.SetTagAsTagGroup(subPath,tg_source.Clone())
else:
tg_dest.DeleteAllTags()
tg_dest.CopyTagsFrom(tg_source.Clone())
#Main Code Starts Here
#Check that we are not running 3.5.0 or 3.5.1 which have a known bug affecting this script.
if (((get_DM_version()[1] == '51') or (get_DM_version()[1] == '50')) and get_DM_version()[0] == "3"):
DM.OkDialog("Due to a bug in DigitalMicrograph 3.5.0 and 3.5.1, this script would cause DM to crash in those versions. \n\nScript Aborted.")
exit()
#Get front image in GMS
img1 = DM.GetFrontImage()
#Get the image window, so we can check if it gets closed
imageDoc = DM.GetFrontImageDocument()
imDocWin = imageDoc.GetWindow()
#Get the image display, for the ROI-removed listener
imageDisplay = img1.GetImageDisplay(0)
#Listeners are started here
#initiate the image listener
listener = CListen(img1)
#check if the source window closes
WindowClosedListenerID = listener.WindowHandleWindowClosedEvent(imDocWin, 'pythonplugin')
#check if the ROI has been deleted
ROIRemovedListenerID = listener.ImageDisplayHandleROIRemovedEvent(imageDisplay,'pythonplugin')
#check if the source image changes
DataChangedListenerID = listener.ImageHandleDataChangedEvent(img1, 'pythonplugin')
#IDs are not used in this script, but could be used to unregister individual listeners in DM 3.5.2 and higher.