@@ -48,51 +48,45 @@ conda activate dsstdeface
4848
4949## Usage
5050
51- To deface anatomical scans in the dataset, run the ` src/dsst_defacing_wf .py ` script. From within the ` dsst-defacing-pipeline ` cloned directory, run the following command to see the help message.
51+ To deface anatomical scans in the dataset, run the ` src/run .py ` script. From within the ` dsst-defacing-pipeline ` cloned directory, run the following command to see the help message.
5252
5353``` text
5454% python src/run.py -h
5555
56- usage: dsst_defacing_wf.py [-h] [-n N_CPUS]
57- [-p PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
58- [-s SESSION_ID [SESSION_ID ...]]
59- [--no-clean]
60- bids_dir output_dir
56+ usage: run.py [-h] [-n N_CPUS] [-p PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
57+ [-s SESSION_ID [SESSION_ID ...]] [--no-clean]
58+ bids_dir output_dir
6159
62- Deface anatomical scans for a given BIDS dataset or a subject
63- directory in BIDS format.
60+ Deface anatomical scans for a given BIDS dataset or a subject directory in
61+ BIDS format.
6462
6563positional arguments:
66- bids_dir The directory with the input dataset
67- formatted according to the BIDS standard.
68- output_dir The directory where the output files should
69- be stored.
64+ bids_dir The directory with the input dataset formatted
65+ according to the BIDS standard.
66+ output_dir The directory where the output files should be stored.
7067
71- options :
68+ optional arguments :
7269 -h, --help show this help message and exit
7370 -n N_CPUS, --n-cpus N_CPUS
74- Number of parallel processes to run when
75- there is more than one folder. Defaults to
76- 1, meaning "serial processing".
71+ Number of parallel processes to run when there is more
72+ than one folder. Defaults to 1, meaning "serial
73+ processing".
7774 -p PARTICIPANT_LABEL [PARTICIPANT_LABEL ...], --participant-label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]
78- The label(s) of the participant(s) that
79- should be defaced. The label corresponds to
80- sub-<participant_label> from the BIDS spec
81- (so it does not include "sub-"). If this
82- parameter is not provided all subjects
83- should be analyzed. Multiple participants
84- can be specified with a space separated
85- list.
86- -s SESSION_ID [SESSION_ID ...], --session-id SESSION_ID [SESSION_ID ...]
87- The ID(s) of the session(s) that should be
75+ The label(s) of the participant(s) that should be
8876 defaced. The label corresponds to
89- ses-<session_id> from the BIDS spec (so it
90- does not include "ses-"). If this parameter
91- is not provided all subjects should be
92- analyzed. Multiple sessions can be specified
93- with a space separated list.
94- --no-clean If this argument is provided, then AFNI
95- intermediate files are preserved.
77+ sub-<participant_label> from the BIDS spec (so it does
78+ not include "sub-"). If this parameter is not provided
79+ all subjects should be analyzed. Multiple participants
80+ can be specified with a space separated list.
81+ -s SESSION_ID [SESSION_ID ...], --session-id SESSION_ID [SESSION_ID ...]
82+ The ID(s) of the session(s) that should be defaced.
83+ The label corresponds to ses-<session_id> from the
84+ BIDS spec (so it does not include "ses-"). If this
85+ parameter is not provided all subjects should be
86+ analyzed. Multiple sessions can be specified with a
87+ space separated list.
88+ --no-clean If this argument is provided, then AFNI intermediate
89+ files are preserved.
9690```
9791
9892The script can be run serially on a BIDS dataset or in parallel at subject/session level. Both these methods of running
@@ -103,7 +97,7 @@ the script have been described below with example commands.
10397If you have a small dataset with less than 10 subjects, then it might be easiest to run the defacing algorithm serially.
10498
10599``` bash
106- python src/dsst_defacing_wf .py ${INPUT_DIR} ${OUTPUT_DIR}
100+ python src/run .py ${INPUT_DIR} ${OUTPUT_DIR}
107101```
108102
109103### Option 2: Parallel defacing
@@ -112,7 +106,7 @@ If you have dataset with over 10 subjects and since each defacing job is indepen
112106subject/session in the dataset using the ` -n/--n-cpus ` option. The following example command will run the pipeline occupying 10 processors at a time.
113107
114108``` bash
115- python src/dsst_defacing_wf .py ${INPUT_DIR} ${OUTPUT_DIR} -n 10
109+ python src/run .py ${INPUT_DIR} ${OUTPUT_DIR} -n 10
116110```
117111
118112Additionally, the pipeline can be run on a single subject or session using the ` -p/--participant-label ` and ` -s/--session-id ` , respectively.
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