Spaces:
Running
Running
| from step1_init_data_list import ( | |
| list_img_ad_from_anish_csv, | |
| list_img_pID_from_synthrad_folder, | |
| ) | |
| def run(): | |
| number = 1 | |
| dataset='anish' | |
| if dataset=='anish': | |
| data_dir = 'D:\Projects\SynthRad\synthrad_conversion\healthy_dissec_home.csv' | |
| target_file_list, _ =list_img_ad_from_anish_csv(data_dir) # a csv_file | |
| elif dataset=='synthrad': | |
| data_dir = 'D:\Projects\data\synthrad\train\Task1\pelvis' | |
| target_file_list, _=list_img_pID_from_synthrad_folder(data_dir, accepted_modalities='ct', saved_name="target_filenames.txt") | |
| create_segmentation(target_file_list[0: number]) | |
| def create_segmentation(dataset_list): | |
| import nibabel as nib | |
| try: | |
| from totalsegmentator.python_api import totalsegmentator | |
| for sample in dataset_list: | |
| input_path=sample | |
| print(f'create segmentation mask for {input_path}') | |
| output_path=input_path.replace('.nii','_seg.nii') | |
| input_img = nib.load(input_path) | |
| totalsegmentator(input=input_img, output=output_path, task='total', fast=False, ml=True) | |
| print(f'segmentation mask is saved as {output_path}') | |
| except: | |
| print("An exception occurred") |