def main(argv=None): """ Main function :param argv: :return: """ parser = get_parser() arguments = parser.parse_args(argv if argv else ['--help']) verbose = arguments.v set_global_loglevel(verbose=verbose) # initialize ImageCropper cropper = ImageCropper(Image(arguments.i)) cropper.verbose = verbose # Switch across cropping methods if arguments.g: cropper.get_bbox_from_gui() elif arguments.m: cropper.get_bbox_from_mask(Image(arguments.m)) elif arguments.ref: cropper.get_bbox_from_ref(Image(arguments.ref)) else: cropper.get_bbox_from_minmax( BoundingBox(arguments.xmin, arguments.xmax, arguments.ymin, arguments.ymax, arguments.zmin, arguments.zmax) ) # Crop image img_crop = cropper.crop(background=arguments.b) # Write cropped image to file if arguments.o is None: fname_out = add_suffix(arguments.i, '_crop') else: fname_out = arguments.o img_crop.save(fname_out) display_viewer_syntax([arguments.i, fname_out])
def main(args=None): """ Main function :param args: :return: """ # get parser args if args is None: args = None if sys.argv[1:] else ['--help'] parser = get_parser() arguments = parser.parse_args(args=args) # initialize ImageCropper cropper = ImageCropper(Image(arguments.i)) cropper.verbose = arguments.v init_sct(log_level=cropper.verbose, update=True) # Update log level # Switch across cropping methods if arguments.g: cropper.get_bbox_from_gui() elif arguments.m: cropper.get_bbox_from_mask(Image(arguments.m)) elif arguments.ref: cropper.get_bbox_from_ref(Image(arguments.ref)) else: cropper.get_bbox_from_minmax( BoundingBox(arguments.xmin, arguments.xmax, arguments.ymin, arguments.ymax, arguments.zmin, arguments.zmax)) # Crop image img_crop = cropper.crop(background=arguments.b) # Write cropped image to file if arguments.o is None: fname_out = sct.add_suffix(arguments.i, '_crop') else: fname_out = arguments.o img_crop.save(fname_out) sct.display_viewer_syntax([arguments.i, fname_out])
def apply(self): # Initialization fname_src = self.input_filename # source image (moving) list_warp = self.list_warp # list of warping fields fname_out = self.output_filename # output fname_dest = self.fname_dest # destination image (fix) verbose = self.verbose remove_temp_files = self.remove_temp_files crop_reference = self.crop # if = 1, put 0 everywhere around warping field, if = 2, real crop interp = sct.get_interpolation('isct_antsApplyTransforms', self.interp) # Parse list of warping fields sct.printv('\nParse list of warping fields...', verbose) use_inverse = [] fname_warp_list_invert = [] # list_warp = list_warp.replace(' ', '') # remove spaces # list_warp = list_warp.split(",") # parse with comma for idx_warp, path_warp in enumerate(self.list_warp): # Check if this transformation should be inverted if path_warp in self.list_warpinv: use_inverse.append('-i') # list_warp[idx_warp] = path_warp[1:] # remove '-' fname_warp_list_invert += [[ use_inverse[idx_warp], list_warp[idx_warp] ]] else: use_inverse.append('') fname_warp_list_invert += [[path_warp]] path_warp = list_warp[idx_warp] if path_warp.endswith((".nii", ".nii.gz")) \ and Image(list_warp[idx_warp]).header.get_intent()[0] != 'vector': raise ValueError("Displacement field in {} is invalid: should be encoded" \ " in a 5D file with vector intent code" \ " (see https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h" \ .format(path_warp)) # need to check if last warping field is an affine transfo isLastAffine = False path_fname, file_fname, ext_fname = sct.extract_fname( fname_warp_list_invert[-1][-1]) if ext_fname in ['.txt', '.mat']: isLastAffine = True # check if destination file is 3d if not sct.check_if_3d(fname_dest): sct.printv('ERROR: Destination data must be 3d') # N.B. Here we take the inverse of the warp list, because sct_WarpImageMultiTransform concatenates in the reverse order fname_warp_list_invert.reverse() fname_warp_list_invert = functools.reduce(lambda x, y: x + y, fname_warp_list_invert) # Extract path, file and extension path_src, file_src, ext_src = sct.extract_fname(fname_src) path_dest, file_dest, ext_dest = sct.extract_fname(fname_dest) # Get output folder and file name if fname_out == '': path_out = '' # output in user's current directory file_out = file_src + '_reg' ext_out = ext_src fname_out = os.path.join(path_out, file_out + ext_out) # Get dimensions of data sct.printv('\nGet dimensions of data...', verbose) img_src = Image(fname_src) nx, ny, nz, nt, px, py, pz, pt = img_src.dim # nx, ny, nz, nt, px, py, pz, pt = sct.get_dimension(fname_src) sct.printv( ' ' + str(nx) + ' x ' + str(ny) + ' x ' + str(nz) + ' x ' + str(nt), verbose) # if 3d if nt == 1: # Apply transformation sct.printv('\nApply transformation...', verbose) if nz in [0, 1]: dim = '2' else: dim = '3' sct.run([ 'isct_antsApplyTransforms', '-d', dim, '-i', fname_src, '-o', fname_out, '-t' ] + fname_warp_list_invert + ['-r', fname_dest] + interp, verbose=verbose, is_sct_binary=True) # if 4d, loop across the T dimension else: dim = '4' path_tmp = sct.tmp_create(basename="apply_transfo", verbose=verbose) # convert to nifti into temp folder sct.printv( '\nCopying input data to tmp folder and convert to nii...', verbose) img_src.save(os.path.join(path_tmp, "data.nii")) sct.copy(fname_dest, os.path.join(path_tmp, file_dest + ext_dest)) fname_warp_list_tmp = [] for fname_warp in list_warp: path_warp, file_warp, ext_warp = sct.extract_fname(fname_warp) sct.copy(fname_warp, os.path.join(path_tmp, file_warp + ext_warp)) fname_warp_list_tmp.append(file_warp + ext_warp) fname_warp_list_invert_tmp = fname_warp_list_tmp[::-1] curdir = os.getcwd() os.chdir(path_tmp) # split along T dimension sct.printv('\nSplit along T dimension...', verbose) im_dat = Image('data.nii') im_header = im_dat.hdr data_split_list = sct_image.split_data(im_dat, 3) for im in data_split_list: im.save() # apply transfo sct.printv('\nApply transformation to each 3D volume...', verbose) for it in range(nt): file_data_split = 'data_T' + str(it).zfill(4) + '.nii' file_data_split_reg = 'data_reg_T' + str(it).zfill(4) + '.nii' status, output = sct.run([ 'isct_antsApplyTransforms', '-d', '3', '-i', file_data_split, '-o', file_data_split_reg, '-t', ] + fname_warp_list_invert_tmp + [ '-r', file_dest + ext_dest, ] + interp, verbose, is_sct_binary=True) # Merge files back sct.printv('\nMerge file back...', verbose) import glob path_out, name_out, ext_out = sct.extract_fname(fname_out) # im_list = [Image(file_name) for file_name in glob.glob('data_reg_T*.nii')] # concat_data use to take a list of image in input, now takes a list of file names to open the files one by one (see issue #715) fname_list = glob.glob('data_reg_T*.nii') fname_list.sort() im_out = sct_image.concat_data(fname_list, 3, im_header['pixdim']) im_out.save(name_out + ext_out) os.chdir(curdir) sct.generate_output_file( os.path.join(path_tmp, name_out + ext_out), fname_out) # Delete temporary folder if specified if int(remove_temp_files): sct.printv('\nRemove temporary files...', verbose) sct.rmtree(path_tmp, verbose=verbose) # Copy affine matrix from destination space to make sure qform/sform are the same sct.printv( "Copy affine matrix from destination space to make sure qform/sform are the same.", verbose) im_src_reg = Image(fname_out) im_src_reg.copy_qform_from_ref(Image(fname_dest)) im_src_reg.save( verbose=0 ) # set verbose=0 to avoid warning message about rewriting file # 2. crop the resulting image using dimensions from the warping field warping_field = fname_warp_list_invert[-1] # if last warping field is an affine transfo, we need to compute the space of the concatenate warping field: if isLastAffine: sct.printv( 'WARNING: the resulting image could have wrong apparent results. You should use an affine transformation as last transformation...', verbose, 'warning') else: if crop_reference in [1, 2]: # Extract only the first ndim of the warping field img_warp = Image(warping_field) if dim == '2': img_warp_ndim = Image(img_src.data[:, :], hdr=img_warp.hdr) elif dim in ['3', '4']: img_warp_ndim = Image(img_src.data[:, :, :], hdr=img_warp.hdr) # Set zero to everything outside the warping field cropper = ImageCropper(Image(fname_out)) cropper.get_bbox_from_ref(img_warp_ndim) if crop_reference == 1: img_out = cropper.crop(background=0) elif crop_reference == 2: img_out = cropper.crop() img_out.save(fname_out) sct.display_viewer_syntax([fname_dest, fname_out], verbose=verbose)