@@ -84,7 +84,7 @@ placeholders for paths to input and output directories, respectively.
8484If you have a small dataset with less than 10 subjects, then it might be easiest to run the defacing algorithm serially.
8585
8686``` bash
87- python dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR}
87+ python dsst-defacing-pipeline/src/ dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR}
8888```
8989
9090#### Option 2: In parallel at subject level
@@ -102,7 +102,7 @@ a. Assuming these scripts are run on the NIH HPC system, the first step would be
102102
103103 for i in ` ls -d ${INPUT_DIR} /sub-* ` ; do \
104104 SUBJ=$( echo $i | sed " s|${INPUT_DIR} /||g" ) ; \
105- echo " python src/dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR} -p ${SUBJ} " ; \
105+ echo " python dsst-defacing-pipeline/ src/dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR} -p ${SUBJ} " ; \
106106 done > defacing_parallel_subject_level.swarm
107107 ```
108108
@@ -126,7 +126,7 @@ for i in `ls -d ${INPUT_DIR}/sub-*`; do
126126 SUBJ=$( echo $i | sed " s|${INPUT_DIR} /||g" ) ;
127127 for j in ` ls -d ${INPUT_DIR} /${SUBJ} /ses-* ` ; do
128128 SESS=$( echo $j | sed " s|${INPUT_DIR} /${SUBJ} /||g" )
129- echo " python src/dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR} -p ${SUBJ} -s ${SESS} " ;
129+ echo " python dsst-defacing-pipeline/ src/dsst_defacing_wf.py -i ${INPUT_DIR} -o ${OUTPUT_DIR} -p ${SUBJ} -s ${SESS} " ;
130130 done ;
131131 done > defacing_parallel_session_level.swarm
132132```
@@ -140,7 +140,7 @@ swarm -f defacing_parallel_session_level.swarm --merge-output --logdir ${OUTPUT_
140140Generate 3D renders for every defaced image in the output directory.
141141
142142 ``` bash
143- python src/generate_renders.py -o ${OUTPUT_DIR}
143+ python dsst-defacing-pipeline/ src/generate_renders.py -o ${OUTPUT_DIR}
144144 ```
145145
146146### Visual Inspection
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