test.py

import funcs
import os
import argparse


parser = argparse.ArgumentParser(description='Limited angle computed tomography')

parser.add_argument('--data_dir', default='./data/level_7',type=str, help='Folder where the input files are located')
parser.add_argument('--out_dir', default='./output/level_7', type=str, help=' Folder where the output files is stored')
parser.add_argument('--group_number', default=7, type=int, help=' Group category number')
parser.add_argument('--method_name', default='BP', type=str, help=' Which method is used before deblurring')
parser.add_argument('--output_size', default=512, type=int, help=' The figure size')
args = parser.parse_args()


if __name__ == "__test__":
    
    group_number=args.group_number
    data_folder=args.data_dir
    output_folder=args.out_dir
    method_name=args.method_name
    output_size=args.output_size
    ##list all files in data folder
    data_list=os.listdir(data_folder)
    ##find all mat files in the list
    data_list=funcs.find_mat(data_list)
    os.environ["CUDA_VISIBLE_DEVICES"]="0"
    ##check whether the list is empty
    if not data_list:
       raise ValueError('There is no mat file in given folder path.') 
    ##reconstruct the phantoms
    # for i in range(len(data_list)):
        #get data path
        # load_file_name=data_list[i]
        # print('processing data:',load_file_name)

        # output_file_name=load_file_name[0:-4]+'.png'
        # data_path=data_folder+load_file_name
        # output_path=output_folder+output_file_name
        #reconstruct
        # funcs.Load_process(data_path,output_path,group_number)        
    if not os.path.exists(output_folder):
        os.mkdir(output_folder)
    funcs.process_testdata(data_folder,output_folder,group_number,method_name,output_size)