def convert_before_saving_as_tiff( image_plus ): # The bUnwarpJ plug-in produces TIFF image stacks consisting of 3 # slices which can be viewed in ImageJ. The 3 slices are: 1) the # registered image, 2) the target image and 3) the black/white warp # image. When running bUnwarpJ from the command line (as these # Galaxy wrappers do) the initial call to IJ.openImage() (to open the # registered source and target images produced by bUnwarpJ) in the # tool's jython_script.py returns an ImagePlus object with a single # slice which is the "generally undesired" slice 3 discussed above. # However, a call to IJ.saveAs() will convert the single-slice TIFF # into a 3-slice TIFF image stack (as described above) if the selected # format for saving is TIFF. Galaxy supports only single-layered # images, so to work around this behavior, we have to convert the # image to something other than TIFF so that slices are eliminated. # We can then convert back to TIFF for saving. There might be a way # to do this without converting twice, but I spent a lot of time looking # and I have yet to discover it. tmp_dir = imagej2_base_utils.get_temp_dir() tmp_out_png_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'png' ) IJ.saveAs( image_plus, 'png', tmp_out_png_path ) return IJ.openImage( tmp_out_png_path )
def convert_before_saving_as_tiff(image_plus): # The bUnwarpJ plug-in produces TIFF image stacks consisting of 3 # slices which can be viewed in ImageJ. The 3 slices are: 1) the # registered image, 2) the target image and 3) the black/white warp # image. When running bUnwarpJ from the command line (as these # Galaxy wrappers do) the initial call to IJ.openImage() (to open the # registered source and target images produced by bUnwarpJ) in the # tool's jython_script.py returns an ImagePlus object with a single # slice which is the "generally undesired" slice 3 discussed above. # However, a call to IJ.saveAs() will convert the single-slice TIFF # into a 3-slice TIFF image stack (as described above) if the selected # format for saving is TIFF. Galaxy supports only single-layered # images, so to work around this behavior, we have to convert the # image to something other than TIFF so that slices are eliminated. # We can then convert back to TIFF for saving. There might be a way # to do this without converting twice, but I spent a lot of time looking # and I have yet to discover it. tmp_dir = imagej2_base_utils.get_temp_dir() tmp_out_png_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'png') IJ.saveAs(image_plus, 'png', tmp_out_png_path) return IJ.openImage(tmp_out_png_path)
parser.add_argument( '--threshold_max', dest='threshold_max', type=float, help='Maximum threshold value' ) parser.add_argument( '--method', dest='method', help='Threshold method' ) parser.add_argument( '--display', dest='display', help='Display mode' ) parser.add_argument( '--black_background', dest='black_background', help='Black background' ) parser.add_argument( '--stack_histogram', dest='stack_histogram', help='Stack histogram' ) parser.add_argument( '--jython_script', dest='jython_script', help='Path to the Jython script' ) parser.add_argument( '--output', dest='output', help='Path to the output file' ) parser.add_argument( '--output_datatype', dest='output_datatype', help='Datatype of the output image' ) args = parser.parse_args() tmp_dir = imagej2_base_utils.get_temp_dir() # ImageJ expects valid image file extensions, so the Galaxy .dat extension does not # work for some features. The following creates a symlink with an appropriate file # extension that points to the Galaxy dataset. This symlink is used by ImageJ. tmp_input_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.input, args.input_datatype ) tmp_output_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.output_datatype ) # Define command response buffers. tmp_out = tempfile.NamedTemporaryFile().name tmp_stdout = open( tmp_out, 'wb' ) tmp_err = tempfile.NamedTemporaryFile().name tmp_stderr = open( tmp_err, 'wb' ) # Java writes a lot of stuff to stderr, so we'll specify a file for handling actual errors. error_log = tempfile.NamedTemporaryFile( delete=False ).name # Build the command line. cmd = imagej2_base_utils.get_base_command_imagej2( None, jython_script=args.jython_script ) if cmd is None: imagej2_base_utils.stop_err( "ImageJ not found!" ) cmd += ' %s' % error_log cmd += ' %s' % tmp_input_path cmd += ' %.3f' % args.threshold_min cmd += ' %.3f' % args.threshold_max
parser.add_argument( '--target_out', default=None, help='Output target image' ) parser.add_argument( '--target_out_datatype', default=None, help='Output registered target image format' ) parser.add_argument( '--jython_script', dest='jython_script', help='Path to the Jython script' ) parser.add_argument( '--max_heap_size_type', dest='max_heap_size_type', help='Type (default or megabytes) of max_heap_size value' ) parser.add_argument( '--max_heap_size', dest='max_heap_size', help='Maximum size of the memory allocation pool used by the JVM.' ) args = parser.parse_args() if args.source_trans_out is not None and args.target_trans_out is not None: save_transformation = True else: save_transformation = False tmp_dir = imagej2_base_utils.get_temp_dir() source_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.source_image, args.source_image_format ) tmp_source_out_tiff_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'tiff' ) tmp_source_out_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.source_out_datatype ) target_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.target_image, args.target_image_format ) if not args.mono: tmp_target_out_tiff_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'tiff' ) tmp_target_out_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.target_out_datatype ) if args.source_mask is not None and args.target_mask is not None: tmp_source_mask_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.source_mask, args.source_mask_format ) tmp_target_mask_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.target_mask, args.target_mask_format ) if save_transformation: # bUnwarpJ automatically names the transformation files based on the names # of the source and target image file names. We've defined symlinks to # temporary files with valid image extensions since ImageJ does not handle # the Galaxy "dataset.dat" file extensions. source_file_name = imagej2_base_utils.get_file_name_without_extension( tmp_source_out_tiff_path ) tmp_source_out_transf_path = os.path.join( tmp_dir, '%s_transf.txt' % source_file_name )
parser.add_argument('--raw_transformation', dest='raw_transformation', help='Raw transformation as saved by bUnwarpJ') parser.add_argument('--source_out', help='Output source image') parser.add_argument('--source_out_datatype', help='Output registered source image format') parser.add_argument('--jython_script', dest='jython_script', help='Path to the Jython script') args = parser.parse_args() tmp_dir = imagej2_base_utils.get_temp_dir() source_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.source_image, args.source_image_format) tmp_source_out_tiff_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'tiff') tmp_source_out_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.source_out_datatype) target_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.target_image, args.target_image_format) raw_transformation_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.raw_transformation, 'txt') # Define command response buffers. tmp_out = tempfile.NamedTemporaryFile().name tmp_stdout = open(tmp_out, 'wb') tmp_err = tempfile.NamedTemporaryFile().name tmp_stderr = open(tmp_err, 'wb') # Build the command line to apply the raw transformation. cmd = imagej2_base_utils.get_base_cmd_bunwarpj(None)