Generalize manual correction scripts

.gitignore

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+.DS_Store
+.idea
+*/__pycache__/
+venv/

README.md

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-# manual-correction
+# Manual correction
+
+This repository contains scripts for the manual correction of spinal cord labels. Currently supported labels are: 
+- spinal cord segmentation
+- gray matter segmentation
+- disc labels
+- ponto-medullary junction (PMJ) label
+
+## Installation
+
+```console
+git clone https://github.com/spinalcordtoolbox/manual-correction.git
+cd manual-correction
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+```
+
+## Usage
+
+> **Note** All scripts currently assume BIDS-compliant data. For more information about the BIDS standard, please visit http://bids.neuroimaging.io.
+
+### `package_for_correction.py`
+
+The `package_for_correction.py` script is used to create a zip file containing the processed images and labels 
+(segmentations, disc labels, etc.). The zip file is then sent to the user for manual correction.
+
+This is useful when you need to correct the labels of a large dataset processed on a remote server. In this case, you do
+not need to copy the whole dataset. Instead, only the images and labels that need to be corrected are zipped. The yaml 
+list of images to correct can be obtained from the [SCT QC html report](https://spinalcordtoolbox.com/overview/concepts/inspecting-results-qc-fsleyes.html#how-do-i-use-the-qc-report).
+
+### `manual_correction.py`
+
+The `manual_correction.py` script is used to correct the labels (segmentations, disc labels, etc.) of a dataset. 
+The script takes as input a processed dataset and outputs the corrected labels to `derivatives/labels` folder.
+
+For the correction of spinal cord and gray matter segmentation, you can choose a viewer ([FSLeyes](https://open.win.ox.ac.uk/pages/fsl/fsleyes/fsleyes/userdoc/#), [ITK-SNAP](http://www.itksnap.org/pmwiki/pmwiki.php), [3D Slicer](https://www.slicer.org)).
+
+For the correction of vertebral labeling and ponto-medullary junction (PMJ), [sct_label_utils](https://github.com/spinalcordtoolbox/spinalcordtoolbox/blob/master/spinalcordtoolbox/scripts/sct_label_utils.py) is used.
+
+### `copy_files_to_derivatives.py`
+
+The `copy_files_to_derivatives.py` script is used to copy manually corrected labels (segmentations, disc labels, etc.) 
+from your local `derivatives/labels` folder to the already existing git-annex BIDS dataset's `derivatives/labels` folder.

copy_files_to_derivatives.py

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+#!/usr/bin/env python
+#
+# Copy manually corrected labels (segmentations, vertebral labeling, etc.) from the preprocessed dataset to the
+# git-annex BIDS dataset's derivatives folder
+#
+# Authors: Jan Valosek
+#
+
+import argparse
+import glob
+import os
+import shutil
+import utils
+
+
+def get_parser():
+    """
+    parser function
+    """
+
+    parser = argparse.ArgumentParser(
+        description='Copy manually corrected files (segmentations, vertebral labeling, etc.) from the source '
+                    'preprocessed dataset to the git-annex BIDS derivatives folder',
+        formatter_class=utils.SmartFormatter,
+        prog=os.path.basename(__file__).strip('.py')
+    )
+    parser.add_argument(
+        '-path-in',
+        metavar="<folder>",
+        required=True,
+        type=str,
+        help='Path to the folder with manually corrected files (usually derivatives). The script assumes that labels '
+             'folder is located in the provided folder.'
+    )
+    parser.add_argument(
+        '-path-out',
+        metavar="<folder>",
+        required=True,
+        type=str,
+        help='Path to the BIDS dataset where manually corrected files will be copied. Include also derivatives folder '
+             'in the path. Files will be copied to the derivatives/label folder.'
+    )
+
+    return parser
+
+
+def main():
+
+    # Parse the command line arguments
+    parser = get_parser()
+    args = parser.parse_args()
+
+    # Check if path_in exists
+    if os.path.isdir(args.path_in):
+        path_in = os.path.join(os.path.abspath(args.path_in), 'labels')
+    else:
+        raise NotADirectoryError(f'{args.path_in} does not exist.')
+
+    # Check if path_out exists
+    if os.path.isdir(args.path_out):
+        path_out = os.path.join(os.path.abspath(args.path_out), 'labels')
+    else:
+        raise NotADirectoryError(f'{args.path_out} does not exist.')
+
+    # Loop across files in input dataset
+    for path_file_in in sorted(glob.glob(path_in + '/**/*.nii.gz', recursive=True)):
+        sub, ses, filename, contrast = utils.fetch_subject_and_session(path_file_in)
+        # Construct path for the output file
+        path_file_out = os.path.join(path_out, sub, ses, contrast, filename)
+        # Check if subject's folder exists in the output dataset, if not, create it
+        path_subject_folder_out = os.path.join(path_out, sub, ses, contrast)
+        if not os.path.isdir(path_subject_folder_out):
+            os.makedirs(path_subject_folder_out)
+            print(f'Creating directory: {path_subject_folder_out}')
+        # Copy nii and json files to the output dataset
+        # TODO - consider rsync instead of shutil.copy
+        shutil.copy(path_file_in, path_file_out)
+        print(f'Copying: {path_file_in} to {path_file_out}')
+        path_file_json_in = path_file_in.replace('nii.gz', 'json')
+        path_file_json_out = path_file_out.replace('nii.gz', 'json')
+        shutil.copy(path_file_json_in, path_file_json_out)
+        print(f'Copying: {path_file_json_in} to {path_file_json_out}')
+
+
+if __name__ == '__main__':
+    main()