Updated running scripts for niftymic (target resolution specified) an…

…d nesvor (properly define the slices output folder if specified)
Medical-Image-Analysis-Laboratory · May 15, 2023 · 74f9b69 · 74f9b69
1 parent 0794cc9
commit 74f9b69
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Showing 2 changed files with 17 additions and 7 deletions.
diff --git a/fetal_brain_utils/cli/run_nesvor_from_config.py b/fetal_brain_utils/cli/run_nesvor_from_config.py
@@ -113,12 +113,10 @@ def crop_input(sub, ses, output_path, img_list, mask_list, fake_run):
             imc = crop_path(im, m)
             maskc = crop_path(m, m)
             # Masking
-
             if imc is None:
                 print(f"Skipping image {im_file} (empty crop)")
                 continue
             imc = ni.Nifti1Image(imc.get_fdata() * maskc.get_fdata(), imc.affine)
-            print(im_file, imc.shape)
             ni.save(imc, cropped_im_path)
             ni.save(maskc, cropped_mask_path)
         if imc is not None:
@@ -208,7 +206,7 @@ def iterate_subject(
         img_str = " ".join([str(im) for im in img_list])
         mask_str = " ".join([str(m) for m in mask_list])
         model = output_sub_ses / f"{sub_ses_path}_{run_path}_model.pt"
-        sigmas = output_sub_ses / "slices"
+        sigmas = output_sub_ses / f"slices_run-{run_id}"
         for i, res in enumerate(target_res):
             res_str = str(res).replace(".", "p")
             output_str = (

diff --git a/fetal_brain_utils/cli/run_niftymic.py b/fetal_brain_utils/cli/run_niftymic.py
@@ -63,6 +63,7 @@ def iterate_subject(
     alpha,
     participant_label,
     use_preprocessed,
+    resolution,
     fake_run,
 ):
     if participant_label:
@@ -142,7 +143,9 @@ def iterate_subject(
                 os.makedirs(mask_cropped_path, exist_ok=True)
 
             # Get in-plane resolution to be set as target resolution.
-            resolution = ni.load(img_list[0]).header["pixdim"][1]
+            resolution = (
+                ni.load(img_list[0]).header["pixdim"][1] if resolution is None else resolution
+            )
 
             # Construct the path to each data point and mask in
             # the filesystem of the docker image
@@ -276,6 +279,13 @@ def main(argv=None):
         type=int,
     )
 
+    p.add_argument(
+        "--resolution",
+        default=None,
+        help="Target resolution (default = in-plane resolution)",
+        type=float,
+    )
+
     p.add_argument(
         "--use_preprocessed",
         action="store_true",
@@ -285,21 +295,22 @@ def main(argv=None):
 
     args = p.parse_args(argv)
     data_path = Path(args.data_path).resolve()
-    config = Path(args.config)
+    config = Path(args.config).resolve()
     masks_folder = Path(args.masks_path).resolve()
     out_path = Path(args.out_path).resolve()
     alpha = args.alpha
     participant_label = args.participant_label
     use_preprocessed = args.use_preprocessed
+    resolution = args.resolution
     nprocs = args.nprocs
     fake_run = args.fake_run
 
     # Load a dictionary of subject-session-paths
     # sub_ses_dict = iter_dir(data_path, add_run_only=True)
 
-    bids_layout = BIDSLayout(data_path, validate=True)
+    bids_layout = BIDSLayout(data_path, validate=False)
 
-    with open(data_path / "code" / config, "r") as f:
+    with open(config, "r") as f:
         params = json.load(f)
     # Iterate over all subjects and sessions
     iterate = partial(
@@ -312,6 +323,7 @@ def main(argv=None):
         alpha=alpha,
         participant_label=participant_label,
         use_preprocessed=use_preprocessed,
+        resolution=resolution,
         fake_run=fake_run,
     )
     if nprocs > 1: