import os

import numpy as np

import data_transforms

import pathfinder

import utils

import utils_lung

from configuration import set_configuration, config

from utils_plots import plot_slice_3d_2, plot_2d, plot_2d_4, plot_slice_3d_3

import utils_lung

import lung_segmentation

# set_configuration('configs_seg_scan', 'luna_s_local')

# p_transform = {'patch_size': (416, 416, 416),

#                'mm_patch_size': (416, 416, 416),

#                'pixel_spacing': (1., 1., 1.)

#                }

def test_dsb3d():

    image_dir = utils.get_dir_path('analysis', pathfinder.METADATA_PATH)

    image_dir = image_dir + '/test_luna/'

    utils.auto_make_dir(image_dir)

    #id2zyxd = utils_lung.read_luna_annotations(pathfinder.LUNA_LABELS_PATH)

    # dsb_data_paths = ['problem_patients/154a79706bcecd0402b913d4bee9eed7/', 

    #                     'problem_patients/122c5c959fd98036c9972eec2062dc59/', 

    #                     'problem_patients/0121c2845f2b7df060945b072b2515d7/',

    #                     'problem_patients/081f4a90f24ac33c14b61b97969b7f81/',

    #                     'problem_patients/0030a160d58723ff36d73f41b170ec21/',

    #                     'problem_patients/19f3b4dea7af5d6e13acb472d6af23d8/',

    #                     'problem_patients/17ffaa3e8b53cc48e97fc6b87114e6dd/',

    #                     'problem_patients/15aa585fb2d3018b295df8619f2d1cf7/',

    #                     'problem_patients/14c534e0b7c3176d9106c6215d0aa8c6/',

    #                     'problem_patients/09b1c678fc1009d84a038cd879be4198/',

    #                     'problem_patients/0f5ab1976a1b1ef1c2eb1d340b0ce9c4/',

    #                     'problem_patients/0c98fcb55e3f36d0c2b6507f62f4c5f1/',

    #                     'problem_patients/0c9d8314f9c69840e25febabb1229fa4/']

    # dsb_data_paths = [  'problem_patients/19f3b4dea7af5d6e13acb472d6af23d8/',

    #                     'problem_patients/081f4a90f24ac33c14b61b97969b7f81/',

    #                     'problem_patients/15aa585fb2d3018b295df8619f2d1cf7/',

    #                     'problem_patients/14c534e0b7c3176d9106c6215d0aa8c6/'

    #                     ]

    # new_dsb_data_paths = [  'problem_patients/00cba091fa4ad62cc3200a657aeb957e/',

    #                     'problem_patients/01de8323fa065a8963533c4a86f2f6c1/',

    #                     'problem_patients/02801e3bbcc6966cb115a962012c35df/',

    #                     'problem_patients/07abb7bec548d1c0ccef088ce934e517/',

    #                     'problem_patients/07bca4290a2530091ce1d5f200d9d526/',

    #                     'problem_patients/0ff552aa083ecfabaf1cfd65b0a8e674/',

    #                     'problem_patients/11616de262f844e6542d3c65d9238b6e/',

    #                     'problem_patients/11fe5426ef497bc490b9f1465f1fb25/',

    #                     'problem_patients/122c5c959fd98036c9972eec2062dc59/',

    #                     'problem_patients/14afefc82d992018c485949285d20c03/',

    #                     'problem_patients/14c534e0b7c3176d9106c6215d0aa8c6/',

    #                     'problem_patients/154a79706bcecd0402b913d4bee9eed7/',

    #                     'problem_patients/15aa585fb2d3018b295df8619f2d1cf7/',

    #                     'problem_patients/174a9fc87f54d6def3730954fbafc99d/',

    #                     'problem_patients/17f5ae9fa49c4e47624f344d29bd03eb/',

    #                     'problem_patients/17ffaa3e8b53cc48e97fc6b87114e6dd/',

    #                     'problem_patients/197e035d3aed52b5a2a0de3ee4d5fcea/',

    #                     'problem_patients/199ff05d08ade6e298d37cc542bc3565/',

    #                     'problem_patients/19f3b4dea7af5d6e13acb472d6af23d8/',

    #                     'problem_patients/1b7ca8dad5c36feb0a6abf8079173e22/',

    #                     'problem_patients/1edf5480bf676f8342a7d516bab58fa0/',

    #                     'problem_patients/20c73e37fc89e007ae5b242480830860/',

    #                     'problem_patients/21bdacdcdb87bf401f34d5d582247c77/',

    #                     ]

    dsb_data_paths = [  'problem_patients/51fbac477a3639f983904fc4d42b8c15/'

                        ]

    # candidates = utils.load_pkl(

    #     'problem_patients/11616de262f844e6542d3c65d9238b6e.pkl')

    # candidates = candidates[:4]

    # print candidates

    # print '--------------'

    for k, p in enumerate(dsb_data_paths):

        pid = p.split('/')[-2]

        print pid

        img, pixel_spacing = utils_lung.read_dicom_scan(p)

        lung_mask = lung_segmentation.segment_HU_scan_elias(img, pid=pid, plot=True)

if __name__ == '__main__':

    test_dsb3d()