add config

model_segvol_single.py

@@ -2,6 +2,8 @@ from transformers import PreTrainedModel, PretrainedConfig
 import numpy as np
 import monai.transforms as transforms
 import nibabel as nib
+from scipy import sparse
+import ast
 
 class SegVolConfig(PretrainedConfig):
     model_type = "segvol"
@@ -199,6 +201,13 @@ class SegVolProcessor():
         # transform
         return item['image'], item['label']
 
+    def load_uniseg_case(self, ct_npy_path, gt_npy_path):
+        img_array = np.load(ct_npy_path)
+        allmatrix_sp= sparse.load_npz(gt_npy_path)
+        gt_shape = ast.literal_eval(gt_npy_path.split('.')[-2])
+        gt_array=allmatrix_sp.toarray().reshape(gt_shape)
+        return img_array, gt_array
+
     def ForegroundNorm(self, ct_narray):
         ct_voxel_ndarray = ct_narray.copy()
         ct_voxel_ndarray = ct_voxel_ndarray.flatten()