debugging

SPIDER.py

@@ -431,15 +431,6 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                 k:v for k,v in item.items() if k not in exclude_vars
             }
         
-        # Merge patient records for radiological gradings data
-        grades_dict = {}
-        for patient_id in patient_ids:
-            patient_grades = [
-                x for x in grades_data if x['Patient'] == str(patient_id)
-            ]
-            if patient_grades:
-                grades_dict[str(patient_id)] = patient_grades
-                
         # # Determine maximum number of radiological gradings per patient
         # max_ivd = 0
         # for temp_dict_1 in grades_dict.values():
@@ -447,6 +438,31 @@ class SPIDER(datasets.GeneratorBasedBuilder):
         #         if int(temp_dict_2['IVD label']) > max_ivd:
         #             max_ivd = int(temp_dict_2['IVD label'])
 
+        # Merge patient records for radiological gradings data
+        grades_dict = {}
+        for patient_id in patient_ids:
+            patient_grades = [
+                x for x in grades_data if x['Patient'] == str(patient_id)
+            ]
+            # Pad radiological gradings so that data for all patients have
+            # the same dimensions
+            if len(patient_grades) < MAX_IVD:
+                for i in range(len(patient_grades) + 1, MAX_IVD + 1):
+                    patient_grades.append({
+                        "Patient": f"{patient_id}",
+                        "IVD label": f"{i}",
+                        "Modic": "",
+                        "UP endplate": "",
+                        "LOW endplate": "",
+                        "Spondylolisthesis": "",
+                        "Disc herniation": "",
+                        "Disc narrowing": "",
+                        "Disc bulging": "",
+                        "Pfirrman grade": "",
+                    })
+            assert len(patient_grades) == MAX_IVD, "Rad. gradings not padded correctly"
+            grades_dict[str(patient_id)] = patient_grades
+
         # Import image and mask data
         image_files = [
             file for file in os.listdir(os.path.join(paths_dict['images'], 'images'))
@@ -525,23 +541,6 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                     if k not in ['Patient', 'IVD label']
                 }
                 patient_grades_dict[key] = value
-            
-            print(example, patient_grades_dict)
-            # Pad patient radiological gradings so that data for all patients
-            # have the same dimensions
-            if len(patient_grades_dict) < MAX_IVD:
-                for i in range(len(patient_grades_dict) + 1, MAX_IVD + 1):
-                    print(i)
-                    patient_grades_dict[f'IVD{i}'] = {
-                        "Modic": "",
-                        "UP endplate": "",
-                        "LOW endplate": "",
-                        "Spondylolisthesis": "",
-                        "Disc herniation": "",
-                        "Disc narrowing": "",
-                        "Disc bulging": "",
-                        "Pfirrman grade": "",
-                    }
 
             # Prepare example return dict
             return_dict = {'patient_id':patient_id, 'scan_type':scan_type}