Fixed generator and added generate_examples method

AeroPath.py

@@ -82,6 +82,8 @@ class AeroPath(datasets.GeneratorBasedBuilder):
 
     DEFAULT_CONFIG_NAME = "zenodo"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
+    self.data_dir = None
+
     def get_data_paths(self):
         return
 
@@ -94,9 +96,9 @@ class AeroPath(datasets.GeneratorBasedBuilder):
         if self.config.name == "zenodo":  # This is the name of the configuration selected in BUILDER_CONFIGS above
             features = datasets.Features(
                 {
-                    "sentence": datasets.Value("string"),
-                    "option1": datasets.Value("string"),
-                    "answer": datasets.Value("string")
+                    "ct": datasets.Value("string"),
+                    "airways": datasets.Value("string"),
+                    "lungs": datasets.Value("string")
                     # These are the features of your dataset like images, labels ...
                 }
             )
@@ -118,6 +120,9 @@ class AeroPath(datasets.GeneratorBasedBuilder):
             # Citation for the dataset
             citation=_CITATION,
         )
+
+    def get_data_dir(self):
+        return self.data_dir
     
     def _split_generators(self, dl_manager):
         # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
@@ -127,9 +132,29 @@ class AeroPath(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         urls = _URLS[self.config.name]
-        data_dir = dl_manager.download_and_extract(urls)
-
-        print("data_dir:", data_dir)
-
-        return [os.path.join(data_dir, x) for x in os.listdir(data_dir)]
+        self.data_dir = dl_manager.download_and_extract(urls)
+
+        print("data_dir:", self.data_dir)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "split": "test",
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, split):
+        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+        for patient_id in os.listdir(self.data_dir):
+            curr_path = os.path.join(self.data_dir, patient_id)
+            yield patient_id, {
+                "ct": os.path.join(curr_path, patient_id, "_CT_HR.nii.gz")
+                "airways": os.path.join(curr_path, patient_id, "_CT_HR_label_airways.nii.gz")
+                "lungs": os.path.join(curr_path, patient_id, "_CT_HR_label_lungs.nii.gz")
+            }