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#!/usr/bin/env python

# =============================================================================================
# DeepFinder - a deep learning approach to localize macromolecules in cryo electron tomograms
# =============================================================================================
# Copyright (C) Inria,  Emmanuel Moebel, Charles Kervrann, All Rights Reserved, 2015-2021, v1.0
# License: GPL v3.0. See <https://www.gnu.org/licenses/>
# =============================================================================================

import os
import sys
from os.path import dirname, abspath, join, basename
import argparse

# Set deepfindHome to the location of this file
deepfindHome = dirname(abspath(__file__))
deepfindHome = os.path.split(deepfindHome)[0]+'/'
sys.path.append(deepfindHome)

# Define arguments:
parser = argparse.ArgumentParser(description='Segment a tomogram.')
parser.add_argument('-t', action='store', dest='path_tomo', help = 'path to tomogram')
parser.add_argument('-w', action='store', dest='path_weights', help = 'path to network weights')
parser.add_argument('-c', action='store', dest='nclass', type=int, help = 'number of classes')
parser.add_argument('-p', action='store', dest='psize', type=int, help = 'patch size, must be multiple of 4')
parser.add_argument('-o', action='store', dest='path_output', help = 'output path')
parser.add_argument('-bin', action='store_true', help='bin resulting segmentation')
args = parser.parse_args()

no_args = args.path_tomo==None and args.path_weights==None and args.nclass==None and args.psize==None and args.path_output==None
incomplete_args = args.path_tomo==None or args.path_weights==None or args.nclass==None or args.psize==None or args.path_output==None

if no_args: # if no args are passed, then open GUI
    gui_folder = 'pyqt/segment/'
    gui_script = 'gui_segment.py'

    cmd = 'cd '+deepfindHome+gui_folder+' ; python '+gui_script
    os.system(cmd)
elif incomplete_args:
    print('DeepFinder message: an argument is missing. All arguments need to be addressed: -t, -w, -c, -p, -o')
else:
    from deepfinder.utils import smap as sm
    from deepfinder.inference import Segment
    import deepfinder.utils.common as cm

    # Load data:
    tomo = cm.read_array(args.path_tomo)

    # Initialize segmentation task:
    seg = Segment(Ncl=args.nclass, path_weights=args.path_weights, patch_size=args.psize)

    # Segment tomogram:
    scoremaps = seg.launch(tomo)

    # Get labelmap from scoremaps:
    labelmap = sm.to_labelmap(scoremaps)

    # Save labelmap:
    cm.write_array(labelmap, args.path_output)

    # Get binned labelmap and save:
    if args.bin:
        s = os.path.splitext(args.path_output)
        scoremapsB = sm.bin(scoremaps)
        labelmapB = sm.to_labelmap(scoremapsB)
        cm.write_array(labelmapB, s[0] + '_binned' + s[1])