file for loading data with HF datasets load_dataset() module

hurricane/dataset.py

@@ -0,0 +1,63 @@
+import os
+import datasets
+
+class HurricaneDetection(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        """
+        Defines the dataset metadata and feature structure.
+        """
+        return datasets.DatasetInfo(
+            description="Dataset containing .nc files for training.",
+            features=datasets.Features({
+                "file_path": datasets.Value("string"),  # Store file paths
+            }),
+            supervised_keys=None,  # Update if supervised task is defined
+            homepage="https://huggingface.co/datasets/nasa-impact/WINDSET/tree/main/hurricane",
+            license="MIT",
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        Define the dataset splits for train.
+        """
+        # Define the directory containing the dataset
+        data_dir = os.path.join(os.getcwd(), "hurricane")  # Update with the actual directory
+
+        # Get the directory for the train split (no validation or test splits)
+        train_dir = os.path.join(data_dir)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"split_dir": train_dir},
+            ),
+        ]
+
+    def _generate_data_from_files(self, data_dir):
+        """
+        Generate file paths for each .h5 file in the directory.
+        """
+        example_id = 0
+
+        # Loop through the files in the directory
+        for h5_file in os.listdir(data_dir):
+
+            if h5_file.endswith(".h5"):  
+                h5_file_path = os.path.join(data_dir, h5_file)
+
+                yield example_id, {
+                    "file_path": h5_file_path,
+                }
+                example_id += 1
+            else:
+                pass
+
+    def _generate_examples(self, split_dir):
+        """
+        Generates examples for the dataset from the split directory.
+        """
+        # Call the data generator to get the file paths
+        for example_id, example in self._generate_data_from_files(split_dir):
+            yield example_id, example