Merge branch 'intensity-masking' of https://github.com/computational-cell-analytics/lightsheet-moser into intensity-masking

Author: constantinpape

scripts/la-vision/postprocess_stardist.py

@@ -0,0 +1,35 @@
+import os
+from glob import glob
+
+from tifffile import imread, imwrite
+from csbdeep.utils import normalize
+from stardist.models import StarDist3D
+
+model = StarDist3D.from_pretrained("3D_demo")
+
+
+def segment_with_stardist(ff, out):
+    axis_norm = (0, 1, 2)  # normalize channels independently
+    x = imread(ff)
+    img = normalize(x[0], 1, 99.8, axis=axis_norm)
+    labels, details = model.predict_instances(img)
+    imwrite(out, labels)
+
+
+def main():
+    direc = "/mnt/vast-nhr/projects/nim00007/data/moser/predictions/sgn-new"
+    out_folder = "/mnt/vast-nhr/projects/nim00007/data/moser/cochlea-lightsheet/predictions/stardist"
+
+    files = [entry.path for entry in os.scandir(direc) if ".tif" in entry.name]
+    files.sort()
+    file_names = [entry.name.split(".tif")[0] for entry in os.scandir(direc) if ".tif" in entry.name]
+    file_names.sort()
+
+    os.makedirs(out_folder, exist_ok=True)
+    for f_path, f_name in zip(files, file_names):
+        out = os.path.join(out_folder, f"{f_name}_seg.tif")
+        segment_with_stardist(f_path, out)
+
+
+if __name__ == "__main__":
+    main()