converted data types

SPIDER.py

@@ -15,6 +15,7 @@
 
 # Import packages
 import csv
+import json
 import os
 from typing import Dict, List, Mapping, Optional, Sequence, Set, Tuple, Union
 
@@ -64,7 +65,9 @@ MAX_IVD = 9
 DEFAULT_SCAN_TYPES = ['t1', 't2', 't2_SPACE']
 DEFAULT_RESIZE = (512, 512, 30)
 DEMO_SUBSET_N = 10
-
+with open("TextFiles/var_types.json", "r") as io:
+    VAR_TYPES = json.load(io)
+    
 _CITATION = """\
 @misc{vandergraaf2023lumbar,
       title={Lumbar spine segmentation in MR images: a dataset and a public benchmark}, 
@@ -197,46 +200,47 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             "mask": datasets.Array3D(shape=self.config.resize_shape, dtype='uint8'),
             "image_path": datasets.Value("string"),
             "mask_path": datasets.Value("string"),
-            "metadata": {
-                "num_vertebrae": datasets.Value("int16"),
-                "num_discs": datasets.Value("int16"),
-                "sex": datasets.Value("string"),
-                "birth_date": datasets.Value("date32"),
-                "AngioFlag": datasets.Value("string"),
-                "BodyPartExamined": datasets.Value("string"),
-                "DeviceSerialNumber": datasets.Value("string"),
-                "EchoNumbers": datasets.Value("float32"),
-                "EchoTime": datasets.Value("float32"),
-                "EchoTrainLength": datasets.Value("float32"),
-                "FlipAngle": datasets.Value("float32"),
-                "ImagedNucleus": datasets.Value("string"),
-                "ImagingFrequency": datasets.Value("float32"),
-                "InPlanePhaseEncodingDirection": datasets.Value("string"),
-                "MRAcquisitionType": datasets.Value("string"),
-                "MagneticFieldStrength": datasets.Value("float32"),
-                "Manufacturer": datasets.Value("string"),
-                "ManufacturerModelName": datasets.Value("string"),
-                "NumberOfPhaseEncodingSteps": datasets.Value("int32"),
-                "PercentPhaseFieldOfView": datasets.Value("float64"),
-                "PercentSampling": datasets.Value("float64"),
-                "PhotometricInterpretation": datasets.Value("string"),
-                "PixelBandwidth": datasets.Value("int32"),
-                "PixelSpacing": datasets.Sequence(datasets.Value("float32")),
-                "RepetitionTime": datasets.Value("float64"),
-                "SAR": datasets.Value("float64"),
-                "SamplesPerPixel": datasets.Value("int32"),
-                "ScanningSequence": datasets.Value("string"),
-                "SequenceName": datasets.Value("string"),
-                "SeriesDescription": datasets.Value("string"),
-                "SliceThickness": datasets.Value("float32"),
-                "SoftwareVersions": datasets.Sequence(datasets.Value("string")),
-                "SpacingBetweenSlices": datasets.Value("float32"),
-                "SpecificCharacterSet": datasets.Value("string"),
-                "TransmitCoilName": datasets.Value("string"),
-                "WindowCenter": datasets.Value("float32"),
-                "WindowWidth": datasets.Value("float32"),
-                "OrigSubset":datasets.Value("string"),
-            },
+            "metadata": {k:datasets.Value(v) for k,v in VAR_TYPES['metadata'].items()},
+            #     {
+            #     "num_vertebrae": datasets.Value("int16"),
+            #     "num_discs": datasets.Value("int16"),
+            #     "sex": datasets.Value("string"),
+            #     "birth_date": datasets.Value("string"),
+            #     "AngioFlag": datasets.Value("string"),
+            #     "BodyPartExamined": datasets.Value("string"),
+            #     "DeviceSerialNumber": datasets.Value("string"),
+            #     "EchoNumbers": datasets.Value("float32"),
+            #     "EchoTime": datasets.Value("float32"),
+            #     "EchoTrainLength": datasets.Value("float32"),
+            #     "FlipAngle": datasets.Value("float32"),
+            #     "ImagedNucleus": datasets.Value("string"),
+            #     "ImagingFrequency": datasets.Value("float32"),
+            #     "InPlanePhaseEncodingDirection": datasets.Value("string"),
+            #     "MRAcquisitionType": datasets.Value("string"),
+            #     "MagneticFieldStrength": datasets.Value("float32"),
+            #     "Manufacturer": datasets.Value("string"),
+            #     "ManufacturerModelName": datasets.Value("string"),
+            #     "NumberOfPhaseEncodingSteps": datasets.Value("int32"),
+            #     "PercentPhaseFieldOfView": datasets.Value("float64"),
+            #     "PercentSampling": datasets.Value("float64"),
+            #     "PhotometricInterpretation": datasets.Value("string"),
+            #     "PixelBandwidth": datasets.Value("int32"),
+            #     "PixelSpacing": datasets.Sequence(datasets.Value("float32")),
+            #     "RepetitionTime": datasets.Value("float64"),
+            #     "SAR": datasets.Value("float64"),
+            #     "SamplesPerPixel": datasets.Value("int32"),
+            #     "ScanningSequence": datasets.Value("string"),
+            #     "SequenceName": datasets.Value("string"),
+            #     "SeriesDescription": datasets.Value("string"),
+            #     "SliceThickness": datasets.Value("float32"),
+            #     "SoftwareVersions": datasets.Sequence(datasets.Value("string")),
+            #     "SpacingBetweenSlices": datasets.Value("float32"),
+            #     "SpecificCharacterSet": datasets.Value("string"),
+            #     "TransmitCoilName": datasets.Value("string"),
+            #     "WindowCenter": datasets.Value("float32"),
+            #     "WindowWidth": datasets.Value("float32"),
+            #     "OrigSubset":datasets.Value("string"),
+            # },
             "rad_gradings": {
                 "IVD label": datasets.Sequence(datasets.Value("string")),
                 "Modic": datasets.Sequence(datasets.Value("string")),
@@ -356,7 +360,7 @@ class SPIDER(datasets.GeneratorBasedBuilder):
         # Import patient/scanner data and radiological gradings data
         overview_data = import_csv_data(paths_dict['overview'])
         grades_data = import_csv_data(paths_dict['gradings'])
-        
+
         # Convert overview data list of dicts to dict of dicts
         exclude_vars = ['new_file_name', 'subset'] # Original data only lists train and validate
         overview_dict = {}
@@ -367,6 +371,22 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             }
             overview_dict[key]['OrigSubset'] = item['subset'] # Change name to original subset
 
+        # Convert overview data types
+        cast_overview_dict = {}
+        for scan_id, scan_metadata in overview_dict.items():
+            cast_dict = {}
+            for key, value in scan_metadata.items():
+                if key in VAR_TYPES['metadata']:
+                    new_type = VAR_TYPES['metadata'][key]
+                    if new_type != "string":
+                        cast_dict[key] = eval(f'np.{new_type}({value})')
+                    else:
+                        cast_dict[key] = str(value)
+                else:
+                    cast_dict[key] = value
+            cast_overview_dict[scan_id] = cast_dict
+        overview_dict = cast_overview_dict
+
         # Merge patient records for radiological gradings data
         grades_dict = {}
         for patient_id in patient_ids: