--- a +++ b/luna_test_patient_segment.py @@ -0,0 +1,59 @@ +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_luna3d(): + 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) + + luna_data_paths = [ + 'problem_patients/1.3.6.1.4.1.14519.5.2.1.6279.6001.877026508860018521147620598474.mhd'] + + candidates = utils.load_pkl( + 'problem_patients/1.3.6.1.4.1.14519.5.2.1.6279.6001.877026508860018521147620598474.pkl') + + candidates = candidates[:4] + print candidates + print '--------------' + print id2zyxd['1.3.6.1.4.1.14519.5.2.1.6279.6001.877026508860018521147620598474'] + + for k, p in enumerate(luna_data_paths): + id = os.path.basename(p).replace('.mhd', '') + print id + img, origin, pixel_spacing = utils_lung.read_mhd(p) + lung_mask = lung_segmentation.segment_HU_scan_elias(img) + x, annotations_tf, tf_matrix, lung_mask_out = data_transforms.transform_scan3d(data=img, + pixel_spacing=pixel_spacing, + p_transform=p_transform, + luna_annotations=candidates, + p_transform_augment=None, + luna_origin=origin, + lung_mask=lung_mask, + world_coord_system=False) + + for zyxd in annotations_tf: + plot_slice_3d_2(x, lung_mask_out, 0, id, img_dir='./', idx=zyxd) + plot_slice_3d_2(x, lung_mask_out, 1, id, img_dir='./', idx=zyxd) + plot_slice_3d_2(x, lung_mask_out, 2, id, img_dir='./', idx=zyxd) + + +if __name__ == '__main__': + test_luna3d()