added raw image and mask objects

SPIDER.py

@@ -24,6 +24,7 @@ import numpy as np
 import pandas as pd
 
 import datasets
+import PIL
 import skimage
 import SimpleITK as sitk
 
@@ -110,7 +111,7 @@ class CustomBuilderConfig(datasets.BuilderConfig):
 class SPIDER(datasets.GeneratorBasedBuilder):
     """TODO: Short description of my dataset."""
 
-    DEFAULT_WRITER_BATCH_SIZE = 64
+    DEFAULT_WRITER_BATCH_SIZE = 16 # PyArrow default is too large for image data
 
     VERSION = datasets.Version("1.1.0")
 
@@ -169,9 +170,9 @@ class SPIDER(datasets.GeneratorBasedBuilder):
         features = datasets.Features({
             "patient_id": datasets.Value("string"),
             "scan_type": datasets.Value("string"),
-            # "raw_image": datasets.Image(),
+            "raw_image": datasets.Image(decode=False),
+            "raw_mask": datasets.Image(decode=False),
             "image_array": datasets.Array3D(shape=image_size, dtype='float64'),
-            # "raw_mask": datasets.Image(),
             "mask_array": datasets.Array3D(shape=image_size, dtype='float64'),
             "metadata": {
                 "num_vertebrae": datasets.Value(dtype="string"), #TODO: more specific types
@@ -478,20 +479,34 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             image_path = os.path.join(paths_dict['images'], 'images', example)
             image = sitk.ReadImage(image_path)
             
+            # Convert .mha image to original size numeric array
+            image_array_original = sitk.GetArrayFromImage(image)
+            
             # Convert .mha image to standardized numeric array
-            image_array = standardize_3D_image(
-                sitk.GetArrayFromImage(image), resize_shape
+            image_array_standardized = standardize_3D_image(
+                image_array_original,
+                resize_shape,
             )
 
+            # Create PIL image object of original image
+            PIL_original_image = PIL.Image.fromarray(image_array_original)
+
             # Load .mha mask file
             mask_path = os.path.join(paths_dict['masks'], 'masks', example)
             mask = sitk.ReadImage(mask_path)
             
+            # Convert .mha mask to original size numeric array
+            mask_array_original = sitk.GetArrayFromImage(mask)
+
             # Convert .mha mask to standardized numeric array
-            mask_array = standardize_3D_image(
-                sitk.GetArrayFromImage(mask), resize_shape
+            mask_array_standardized = standardize_3D_image(
+                mask_array_original,
+                resize_shape,
             )
-    
+
+            # Create PIL image object of original mask
+            PIL_original_mask = PIL.Image.fromarray(mask_array_original)
+
             # Extract overview data corresponding to image
             image_overview = overview_dict[scan_id]
 
@@ -502,13 +517,13 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             return_dict = {
                 'patient_id':patient_id,
                 'scan_type':scan_type,
-                'raw_image':None, #TODO
-                'raw_mask':None, #TODO
-                'image_array':image_array,
-                'mask_array':mask_array,
+                'raw_image':PIL_original_image, 
+                'raw_mask':PIL_original_mask, 
+                'image_array':image_array_standardized,
+                'mask_array':mask_array_standardized,
                 'metadata':image_overview,
                 'rad_gradings':patient_grades_dict,
-                }
+            }
 
             # Yield example
             yield scan_id, return_dict