"""
Benchmark for R package - RNiftyReg
LINKS:
* http://cran.r-project.org/web/packages/RNiftyReg/RNiftyReg.pdf
* https://github.com/jonclayden/RNiftyReg
Installation
------------
1. Install the R environment (https://stackoverflow.com/questions/31114991)::
apt install r-base-core r-base-dev
sudo apt-get -y install libcurl4-gnutls-dev libxml2-dev libssl-dev
2. Run R and install required R packages::
install.packages(c("png", "jpeg", "OpenImageR", "devtools"))
devtools::install_github("jonclayden/RNiftyReg")
Usage
-----
Run the basic R script::
Rscript scripts/Rscript/RNiftyReg_linear.r \
data-images/rat-kidney_/scale-5pc/Rat-Kidney_HE.jpg \
data-images/rat-kidney_/scale-5pc/Rat-Kidney_PanCytokeratin.jpg \
data-images/rat-kidney_/scale-5pc/Rat-Kidney_HE.csv \
output/
Run the RNiftyReg benchmark::
python bm_experiments/bm_rNiftyReg.py \
-t ./data-images/pairs-imgs-lnds_histol.csv \
-d ./data-images \
-o ./results \
-R Rscript \
-script ./scripts/Rscript/RNiftyReg_linear.r
.. note:: tested for RNiftyReg > 2.x
Copyright (C) 2017-2019 Jiri Borovec <jiri.borovec@fel.cvut.cz>
"""
import logging
import os
import shutil
import sys
sys.path += [os.path.abspath('.'), os.path.abspath('..')] # Add path to root
from birl.benchmark import ImRegBenchmark
from birl.utilities.data_io import load_landmarks, save_landmarks
from bm_experiments import bm_comp_perform
class BmRNiftyReg(ImRegBenchmark):
""" Benchmark for R package - RNiftyReg
no run test while this method requires manual installation of RNiftyReg
For the app installation details, see module details.
EXAMPLE
-------
>>> from birl.utilities.data_io import create_folder, update_path
>>> path_out = create_folder('temp_results')
>>> fn_path_conf = lambda n: os.path.join(update_path('scripts'), 'Rscript', n)
>>> path_csv = os.path.join(update_path('data-images'), 'pairs-imgs-lnds_mix.csv')
>>> params = {'path_out': path_out,
... 'path_table': path_csv,
... 'nb_workers': 2,
... 'unique': False,
... 'exec_R': 'Rscript',
... 'path_R_script': fn_path_conf('RNiftyReg_linear.r')}
>>> benchmark = BmRNiftyReg(params)
>>> benchmark.run() # doctest: +SKIP
>>> shutil.rmtree(path_out, ignore_errors=True)
"""
#: required experiment parameters
REQUIRED_PARAMS = ImRegBenchmark.REQUIRED_PARAMS + ['exec_R', 'path_R_script']
#: file with exported image registration time
NAME_FILE_TIME = 'time.txt'
#: file with warped landmarks after performed registration
NAME_FILE_LANDMARKS = 'points.pts'
#: file with warped image after performed registration
NAME_FILE_IMAGE = 'warped.jpg'
def _prepare(self):
logging.info('-> copy configuration...')
self._copy_config_to_expt('path_R_script')
def _generate_regist_command(self, item):
""" generate the registration command(s)
:param dict item: dictionary with registration params
:return str|list(str): the execution commands
"""
path_im_ref, path_im_move, _, path_lnds_move = self._get_paths(item)
path_dir = self._get_path_reg_dir(item) + os.path.sep
cmd = ' '.join([
self.params['exec_R'],
self.params['path_R_script'],
path_im_ref,
path_im_move,
path_lnds_move,
path_dir,
])
return cmd
def _extract_warped_image_landmarks(self, item):
""" get registration results - warped registered images and landmarks
:param dict item: dictionary with registration params
:return dict: paths to warped images/landmarks
"""
logging.debug('.. warp the registered image and get landmarks')
path_dir = self._get_path_reg_dir(item)
_, path_img_move, _, path_lnds_move = self._get_paths(item)
path_lnds_warp, path_img_warp = None, None
# load warped landmarks from TXT
path_lnds = os.path.join(path_dir, self.NAME_FILE_LANDMARKS)
if os.path.isfile(path_lnds):
points_warp = load_landmarks(path_lnds)
path_lnds_warp = os.path.join(path_dir, os.path.basename(path_lnds_move))
save_landmarks(path_lnds_warp, points_warp)
os.remove(path_lnds)
path_regist = os.path.join(path_dir, self.NAME_FILE_IMAGE)
if os.path.isfile(path_regist):
name_img_move, _ = os.path.splitext(os.path.basename(path_img_move))
_, ext_img_warp = os.path.splitext(self.NAME_FILE_IMAGE)
path_img_warp = os.path.join(path_dir, name_img_move + ext_img_warp)
os.rename(path_regist, path_img_warp)
return {
self.COL_IMAGE_MOVE_WARP: path_img_warp,
self.COL_POINTS_MOVE_WARP: path_lnds_warp,
}
def _extract_execution_time(self, item):
""" if needed update the execution time
:param dict item: dictionary with registration params
:return float|None: time in minutes
"""
path_dir = self._get_path_reg_dir(item)
path_time = os.path.join(path_dir, self.NAME_FILE_TIME)
with open(path_time, 'r') as fp:
t_exec = float(fp.read()) / 60.
return t_exec
@staticmethod
def extend_parse(arg_parser):
""" extent the basic arg parses by some extra required parameters
:return object:
"""
# SEE: https://docs.python.org/3/library/argparse.html
arg_parser.add_argument(
'-R', '--exec_R', type=str, required=True, help='path to the Rscript executable', default='Rscript'
)
arg_parser.add_argument(
'-script', '--path_R_script', required=True, type=str, help='path to the R script with registration'
)
return arg_parser
# RUN by given parameters
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO)
logging.info(__doc__)
arg_params, path_expt = BmRNiftyReg.main()
if arg_params.get('run_comp_benchmark', False):
bm_comp_perform.main(path_expt)
