DeepRegNet /
DeepReg
| @@ 103-152 (lines=50) @@ | ||
| 100 | path_to_test = os.path.join(path_to_data_folder, "test") |
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| 101 | path_to_valid = os.path.join(path_to_data_folder, "valid") |
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| 102 | ||
| 103 | if os.path.exists(path_to_test) is not True: |
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| 104 | ||
| 105 | os.mkdir(path_to_test) |
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| 106 | os.mkdir(os.path.join(path_to_test, "fixed_images")) |
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| 107 | os.mkdir(os.path.join(path_to_test, "fixed_labels")) |
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| 108 | os.mkdir(os.path.join(path_to_test, "moving_images")) |
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| 109 | os.mkdir(os.path.join(path_to_test, "moving_labels")) |
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| 110 | ||
| 111 | ratio_of_test_and_valid_samples = 0.4 |
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| 112 | ||
| 113 | unique_case_names = [] |
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| 114 | for file in images_fnames: |
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| 115 | case_name_as_list = file.split("_")[0:2] |
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| 116 | case_name = case_name_as_list[0] + "_" + case_name_as_list[1] |
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| 117 | unique_case_names.append(case_name) |
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| 118 | unique_case_names = np.unique(unique_case_names) |
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| 119 | ||
| 120 | test_and_valid_cases = random.sample( |
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| 121 | list(unique_case_names), |
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| 122 | int(ratio_of_test_and_valid_samples * len(unique_case_names)), |
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| 123 | ) |
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| 124 | test_cases = test_and_valid_cases[ |
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| 125 | 0 : int(int(ratio_of_test_and_valid_samples * len(unique_case_names) / 2)) |
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| 126 | ] |
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| 127 | valid_cases = test_and_valid_cases[ |
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| 128 | int(int(ratio_of_test_and_valid_samples * len(unique_case_names) / 2)) + 1 : |
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| 129 | ] |
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| 130 | ||
| 131 | def move_test_cases_into_correct_path(test_cases, path_to_train, path_to_test): |
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| 132 | folder_names = os.listdir(path_to_train) |
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| 133 | os.chdir(path_to_train) |
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| 134 | for case in test_cases: |
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| 135 | for folder in folder_names: |
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| 136 | file_names = os.listdir(os.path.join(path_to_train, folder)) |
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| 137 | for file in file_names: |
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| 138 | if case in file: |
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| 139 | os.chdir(os.path.join(path_to_train, folder)) |
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| 140 | source = file |
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| 141 | destination = os.path.join(path_to_test, folder) |
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| 142 | shutil.move(source, destination) |
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| 143 | ||
| 144 | move_test_cases_into_correct_path(test_cases, path_to_train, path_to_test) |
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| 145 | ||
| 146 | os.mkdir(path_to_valid) |
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| 147 | os.mkdir(os.path.join(path_to_valid, "fixed_images")) |
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| 148 | os.mkdir(os.path.join(path_to_valid, "fixed_labels")) |
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| 149 | os.mkdir(os.path.join(path_to_valid, "moving_images")) |
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| 150 | os.mkdir(os.path.join(path_to_valid, "moving_labels")) |
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| 151 | ||
| 152 | move_test_cases_into_correct_path(valid_cases, path_to_train, path_to_valid) |
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| 153 | ||
| 154 | ######## NAMING FILES SUCH THAT THEIR NAMES MATCH FOR PAIRING ######## |
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| 155 | ||
| @@ 98-147 (lines=50) @@ | ||
| 95 | path_to_test = os.path.join(path_to_data_folder, "test") |
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| 96 | path_to_valid = os.path.join(path_to_data_folder, "valid") |
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| 97 | ||
| 98 | if os.path.exists(path_to_test) is not True: |
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| 99 | ||
| 100 | os.mkdir(path_to_test) |
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| 101 | os.mkdir(os.path.join(path_to_test, "fixed_images")) |
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| 102 | os.mkdir(os.path.join(path_to_test, "fixed_labels")) |
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| 103 | os.mkdir(os.path.join(path_to_test, "moving_images")) |
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| 104 | os.mkdir(os.path.join(path_to_test, "moving_labels")) |
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| 105 | ||
| 106 | ratio_of_test_and_valid_samples = 0.2 |
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| 107 | ||
| 108 | unique_case_names = [] |
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| 109 | for file in images_fnames: |
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| 110 | case_name_as_list = file.split("_")[0:2] |
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| 111 | case_name = case_name_as_list[0] + "_" + case_name_as_list[1] |
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| 112 | unique_case_names.append(case_name) |
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| 113 | unique_case_names = np.unique(unique_case_names) |
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| 114 | ||
| 115 | test_and_valid_cases = random.sample( |
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| 116 | list(unique_case_names), |
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| 117 | int(ratio_of_test_and_valid_samples * len(unique_case_names)), |
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| 118 | ) |
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| 119 | test_cases = test_and_valid_cases[ |
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| 120 | 0 : int(int(ratio_of_test_and_valid_samples * len(unique_case_names) / 2)) |
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| 121 | ] |
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| 122 | valid_cases = test_and_valid_cases[ |
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| 123 | int(int(ratio_of_test_and_valid_samples * len(unique_case_names) / 2)) + 1 : |
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| 124 | ] |
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| 125 | ||
| 126 | def move_test_cases_into_correct_path(test_cases, path_to_train, path_to_test): |
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| 127 | folder_names = os.listdir(path_to_train) |
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| 128 | os.chdir(path_to_train) |
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| 129 | for case in test_cases: |
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| 130 | for folder in folder_names: |
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| 131 | file_names = os.listdir(os.path.join(path_to_train, folder)) |
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| 132 | for file in file_names: |
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| 133 | if case in file: |
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| 134 | os.chdir(os.path.join(path_to_train, folder)) |
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| 135 | source = file |
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| 136 | destination = os.path.join(path_to_test, folder) |
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| 137 | shutil.move(source, destination) |
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| 138 | ||
| 139 | move_test_cases_into_correct_path(test_cases, path_to_train, path_to_test) |
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| 140 | ||
| 141 | os.mkdir(path_to_valid) |
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| 142 | os.mkdir(os.path.join(path_to_valid, "fixed_images")) |
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| 143 | os.mkdir(os.path.join(path_to_valid, "fixed_labels")) |
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| 144 | os.mkdir(os.path.join(path_to_valid, "moving_images")) |
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| 145 | os.mkdir(os.path.join(path_to_valid, "moving_labels")) |
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| 146 | ||
| 147 | move_test_cases_into_correct_path(valid_cases, path_to_train, path_to_valid) |
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| 148 | ||
| 149 | ######## NAMING FILES SUCH THAT THEIR NAMES MATCH FOR PAIRING ######## |
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| 150 | ||
