also record diameter and size

kimo/2-check-series.py

@@ -22,6 +22,7 @@ INCLUDED_HASH = [
 
 
 LAST_DAY = datetime.datetime.strptime("2025-11-01", "%Y-%m-%d")
+MAX_PATIENT = 10//3
 
 SRC_ROOT = "/mnt/t24/Public/kimo/TSHA"
 RAW_DIR = "/mnt/t24/Public/kimo/raw/"
@@ -217,6 +218,8 @@ def main():
     for patho in sorted(os.listdir(SRC_ROOT)):
         patho_dir = os.path.join(SRC_ROOT, patho)
 
+        num_patient = 0
+
         for patient in sorted(os.listdir(patho_dir)):
             md5, hash = hashptid(patient)
 
@@ -268,7 +271,9 @@ def main():
             if num_study > 0:
                 with open(complete_file, 'w') as f:
                     f.write('done')
-            # break
+                num_patient += 1
+            if num_patient >= MAX_PATIENT:
+                break
         # break
     print(NII_DICT)
     logging.info(f"BodyPartExamined: {BodyPartExamined}")

kimo/4-final-copy.py

@@ -6,6 +6,7 @@ import shutil
 from PIL import Image
 
 import numpy as np
+import pandas as pd
 import SimpleITK as sitk
 
 ROOT_DIR = "/mnt/t24/Public/kimo/"
@@ -99,8 +100,14 @@ def contour_overlay(image_nii, label_nii):
         logging.warning(f"No label found in {label_nii}")
         return None
 
-    print(stats.GetPhysicalSize(1))
-    exit()
+    if stats.GetPhysicalSize(1) < 1000:
+        logging.warning(f"Label size too small in {label_nii}")
+        return None
+
+    # print(stats.GetFeretDiameter(1))
+    # print(stats.GetEquivalentEllipsoidDiameter(1))
+    # print(stats.GetPhysicalSize(1))
+    # exit()
 
     center_idx = largest.TransformPhysicalPointToIndex(stats.GetCentroid(1))
 
@@ -162,9 +169,11 @@ def contour_overlay(image_nii, label_nii):
 
     return {
         'contour_image': Image.fromarray(row_con),
-        'overlay_image': combined_img
+        'overlay_image': combined_img,
+        'stats': stats,
     }
 
+DATALIST = []
 
 def main():
     FORMAT = '%(asctime)s [%(filename)s:%(lineno)d] %(message)s'
@@ -213,10 +222,24 @@ def main():
 
         shutil.copyfile(image_nii, f"{dest_dir}/image.nii.gz")
         shutil.copyfile(label_nii, f"{dest_dir}/label.nii.gz")
-        copytree(dicomdir, f"{dest_dir}/DICOM")
+        # copytree(dicomdir, f"{dest_dir}/DICOM")
 
         CASE_SET.add(hash)
         # exit()
 
+        DATALIST.append({
+            "Category": category,
+            "Stem": stem,
+            "EquivalentEllipsoidDiameter": con_ov['stats'].GetEquivalentEllipsoidDiameter(1),
+            "PhysicalSize": con_ov['stats'].GetPhysicalSize(1),
+            # "dicomdir": dicomdir,
+            # "image_nii": image_nii,
+            # "label_nii": label_nii,
+            # "dest_dir": dest_dir,
+        })
+
+    df = pd.DataFrame(DATALIST)
+    df.to_excel(f"{FINAL_DIR}/datalist.xlsx", index=False)
+
 if __name__ == "__main__":
     main()