import jython_utils
import sys
from ij import IJ
# Fiji Jython interpreter implements Python 2.5 which does not
# provide support for argparse.
error_log = sys.argv[-5]
input = sys.argv[-4]
direction = sys.argv[-3]
tmp_output_path = sys.argv[-2]
output_datatype = sys.argv[-1]
# Open the input image file.
input_image_plus = IJ.openImage(input)
# Create a copy of the image.
input_image_plus_copy = input_image_plus.duplicate()
image_processor_copy = input_image_plus_copy.getProcessor()
try:
# Run the command.
IJ.run(input_image_plus_copy, direction, "")
# Save the ImagePlus object as a new image.
IJ.saveAs(input_image_plus_copy, output_datatype, tmp_output_path)
except Exception, e:
jython_utils.handle_error(error_log, str(e))
elif noise == 'salt_and_pepper':
IJ.run(image_plus_copy, "Salt and Pepper", "")
elif noise == 'despeckle':
IJ.run(image_plus_copy, "Despeckle", "")
elif noise == 'remove_outliers':
IJ.run(image_plus_copy, "Remove Outliers",
"radius=&radius threshold=&threshold which=&which_outliers")
elif noise == 'remove_nans':
if bit_depth == 32:
IJ.run(image_plus_copy, "Remove NaNs", "")
else:
# When Galaxy metadata for images is enhanced to include information like this,
# we'll be able to write tool validators rather than having to stop the job in
# an error state.
msg = "Remove NaNs requires a 32-bit image, the selected image is %d-bit" % bit_depth
jython_utils.handle_error(error_log, msg)
error = True
elif noise == 'rof_denoise':
if image_type == ImagePlus.GRAY32:
IJ.run(image_plus_copy, "ROF Denoise", "")
else:
msg = "ROF Denoise requires an image of type 32-bit grayscale, the selected image is %d-bit" % (
bit_depth)
jython_utils.handle_error(error_log, msg)
error = True
elif noise == 'randomj':
if randomj == 'randomj_binomial':
IJ.run(image_plus_copy, "RandomJ Binomial",
"trials=&trials probability=&probability insertion=&insertion")
elif randomj == 'randomj_exponential':
IJ.run(image_plus_copy, "RandomJ Exponential",
input_image_plus = IJ.openImage( input )
# Create a copy of the image.
input_image_plus_copy = input_image_plus.duplicate()
image_processor_copy = input_image_plus_copy.getProcessor()
try:
# Convert image to binary if necessary.
if not image_processor_copy.isBinary():
# Convert the image to binary grayscale.
IJ.run( input_image_plus_copy, "Make Binary","iterations=1 count=1 edm=Overwrite do=Nothing" )
# Set the options.
if jython_utils.asbool( dark_background ):
method_str = "%s dark" % method
else:
method_str = method
IJ.setAutoThreshold( input_image_plus_copy, method_str )
if display == "red":
display_mode = "Red"
elif display == "bw":
display_mode = "Black & White"
elif display == "over_under":
display_mode = "Over/Under"
IJ.setThreshold( input_image_plus_copy, threshold_min, threshold_max, display_mode )
# Run the command.
IJ.run( input_image_plus_copy, "threshold", "" )
# Save the ImagePlus object as a new image.
IJ.saveAs( input_image_plus_copy, output_datatype, tmp_output_path )
except Exception, e:
jython_utils.handle_error( error_log, str( e ) )
IJ.run( image_plus_copy, "Add Specified Noise", "standard=&standard_deviation" )
elif noise == 'salt_and_pepper':
IJ.run( image_plus_copy, "Salt and Pepper", "" )
elif noise == 'despeckle':
IJ.run( image_plus_copy, "Despeckle", "" )
elif noise == 'remove_outliers':
IJ.run( image_plus_copy, "Remove Outliers", "radius=&radius threshold=&threshold which=&which_outliers" )
elif noise == 'remove_nans':
if bit_depth == 32:
IJ.run( image_plus_copy, "Remove NaNs", "" )
else:
# When Galaxy metadata for images is enhanced to include information like this,
# we'll be able to write tool validators rather than having to stop the job in
# an error state.
msg = "Remove NaNs requires a 32-bit image, the selected image is %d-bit" % bit_depth
jython_utils.handle_error( error_log, msg )
error = True
elif noise == 'rof_denoise':
if image_type == ImagePlus.GRAY32:
IJ.run( image_plus_copy, "ROF Denoise", "" )
else:
msg = "ROF Denoise requires an image of type 32-bit grayscale, the selected image is %d-bit" % ( bit_depth )
jython_utils.handle_error( error_log, msg )
error = True
elif noise == 'randomj':
if randomj == 'randomj_binomial':
IJ.run( image_plus_copy, "RandomJ Binomial", "trials=&trials probability=&probability insertion=&insertion" )
elif randomj == 'randomj_exponential':
IJ.run( image_plus_copy, "RandomJ Exponential", "lambda=&lammbda insertion=&insertion" )
elif randomj == 'randomj_gamma':
IJ.run( image_plus_copy, "RandomJ Gamma", "order=&order insertion=&insertion" )
