def doInBackground(self):
imp = self.imp
print "started"
ts = time.time()
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S')
print st
# Disable frame3 buttons in GUI while loading ROIs
f2_btn_original.setEnabled( 0 )
f2_btn_label.setEnabled( 0 )
f2_btn_prev.setEnabled( 0 )
f2_btn_next.setEnabled( 0 )
RM = RoiManager() # we create an instance of the RoiManager class
rm = RM.getRoiManager() # "activate" the RoiManager otherwise it can behave strangely
rm.reset()
rm.runCommand(imp,"Show All without labels") # we make sure we see the ROIs as they are loading
imp2 = imp.duplicate()
ip = imp2.getProcessor()
width = imp2.getWidth()
height = imp2.getHeight() - 1
max_label = int(imp2.getStatistics().max)
max_digits = int(math.ceil(math.log(max_label,10))) # Calculate the number of digits for the name of the ROI (padding with zeros)
IJ.setForegroundColor(0, 0, 0) # We pick black color to delete the label already computed
for j in range(height):
for i in range(width):
current_pixel_value = ip.getValue(i,j)
if current_pixel_value > 0:
IJ.doWand(imp2, i, j, 0.0, "Legacy smooth");
# We add this ROI to the ROI manager
roi = imp2.getRoi()
roi.setName(str(int(current_pixel_value)).zfill(max_digits))
rm.addRoi(roi)
ip.fill(roi) # Much faster than IJ.run(imp2, "Fill", ....
# Update ProgressBar
progress = int((current_pixel_value / max_label) * 100)
self.super__setProgress(progress)
rm.runCommand(imp,"Sort") # Sort the ROIs in the ROI manager
rm.runCommand(imp,"Show All without labels")
ts = time.time()
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S')
print st
print "Finished"
def doInBackground(self):
try: # In case there is an error, so that FIJI doesn't crash
print "INICIO"
print self.files
print self.pix_erosion_mult
label_files = [f for f in self.files if f.endswith('_label.png') or
f.endswith('_label.tif') or
f.endswith('_label.jpg')]
total_label_files = len(label_files)
print "total label files:"
print total_label_files
gvars["total label files"] = total_label_files
for filenum, f in enumerate(label_files): # Loop through the files in the directory
self.label_update(filenum+1, total_label_files)
label_file = f
print "----"
print label_file
original_name = re.sub(r"_label.*", "",f) # get name of the original image without extension
if (original_name+".tif") in self.files: # for an original image with extension .tif
original_file = original_name+".tif"
print original_file
elif (original_name+".tiff") in self.files: # for an original image with extension .tiff (with double f)
original_file = original_name+".tiff"
print original_file
else: # If there is no original image
original_file = "None"
print original_file
path_multiple = gvars['path_multiple_image_directory']
print path_multiple
########### Section Label To Roi ###########
RM = RoiManager()
rm = RM.getRoiManager()
label_image = IJ.openImage(path_multiple + "\\" + label_file)
rm.reset()
rm.runCommand(label_image,"Show All without labels") # we make sure we see the ROIs as they are loading
imp2 = label_image.duplicate()
ip = imp2.getProcessor()
width = imp2.getWidth()
height = imp2.getHeight() - 1
max_label = int(imp2.getStatistics().max)
max_digits = int(math.ceil(math.log(max_label,10))) # Calculate the number of digits for the name of the ROI (padding with zeros)
IJ.setForegroundColor(0, 0, 0) # We pick black color to delete the label already computed
for j in range(height):
for i in range(width):
current_pixel_value = ip.getValue(i,j)
if current_pixel_value > 0:
IJ.doWand(imp2, i, j, 0.0, "Legacy smooth");
# We add this ROI to the ROI manager
roi = imp2.getRoi()
roi.setName(str(int(current_pixel_value)).zfill(max_digits))
rm.addRoi(roi)
ip.fill(roi) # Much faster than IJ.run(imp2, "Fill", ....
# Update ProgressBar
progress = int((current_pixel_value / max_label) * 100)
self.super__setProgress(progress)
rm.runCommand(label_image,"Sort") # Sort the ROIs in the ROI manager
rm.runCommand(label_image,"Show All without labels")
######### Section ROI erotion #########
for i in range(0, rm.getCount()):
roi = rm.getRoi(i)
new_roi = RoiEnlarger.enlarge(roi, -self.pix_erosion_mult) # Important to use this instead of the IJ.run("Enlarge... much faster!!
rm.setRoi(new_roi,i)
####### Section Save ROIs ##############
print original_name
path_to_multiple_ROIs = str(gvars['path_multiple_image_directory']) + "\\" + original_name + "_Erosion_" +str(self.pix_erosion_mult)+ "px_" + "RoiSet.zip"
print path_to_multiple_ROIs
rm.runCommand("Save", path_to_multiple_ROIs)
print("ROIs saved")
####### Section open Original Image ##############
if original_file != "None": # If there is an original image file besides the label image, we'll measure and generate table of measurements
print "There is an original image associated to this label"
original_image = IJ.openImage(path_multiple + "\\" + original_file)
IJ.run(original_image, "Enhance Contrast", "saturated=0.35")
rm.runCommand(original_image,"Show All without labels")
#original_image.show()
table_message = []
is_scaled = original_image.getCalibration().scaled()
if is_scaled:
spatial_cal = "True"
else:
spatial_cal = "False"
nChannels = original_image.getNChannels()
print "Total channels:"
print nChannels
for current_channel in range(1,nChannels+1):
print "Current channel:"
print current_channel
original_image.setSlice(current_channel)
current_slice = str(original_image.getCurrentSlice()) #Get current slice for saving into filename
print "Current slice:"
print current_slice
IJ.run("Clear Results", "")
rm.runCommand(original_image,"Select All");
rm.runCommand(original_image,"Measure")
table = ResultsTable.getResultsTable().clone()
IJ.selectWindow("Results")
IJ.run("Close")
for i in range(0, table.size()):
table.setValue('File', i, str(original_name))
table.setValue('Channel', i, current_channel)
table.setValue('Pixels_eroded', i, str(self.pix_erosion_mult))
table.setValue('Spatial_calibration', i, spatial_cal)
table.show("Tabla actualizada")
path_to_multiple_Tables = str(gvars['path_multiple_image_directory']) + "\\" + original_name + "_Erosion_" +str(self.pix_erosion_mult)+ "px_Channel_" + str(current_channel) + ".csv"
IJ.saveAs("Results", path_to_multiple_Tables)
# Section Save jpg with outlines
path_to_multiple_outline = str(gvars['path_multiple_image_directory']) + "\\" + original_name + "_Erosion_" +str(self.pix_erosion_mult)+ "px_" + "Outlines.jpg"
outlines_image = original_image.flatten()
IJ.saveAs(outlines_image, "JPG", path_to_multiple_outline)
IJ.run("Close")
else:
print "There is NOT an original image associated to this label"
label_image.close()
####### Section ending ##############
except Exception as e:
print e
