Update dataset.py

dataset.py

@@ -0,0 +1,72 @@
+import datasets
+import h5py
+import json
+import os
+
+class MyDatasetConfig(datasets.BuilderConfig):
+    def __init__(self, name, split_file=None, **kwargs):
+        super().__init__(name=name, **kwargs)
+        self.split_file = split_file
+
+
+class MyDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        MyDatasetConfig(name="Arizona", split_file="Train-Test-Split/split_by_patches_Arizona_split_h5.json"),
+        # Add other state configs similarly
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="Patch-level irrigation dataset stored as separate .h5 files",
+            features=datasets.Features({
+                "id": datasets.Value("string"),
+                "rgb": datasets.Array3D(shape=(None, None, 3), dtype="float32"),
+                "agri_index": datasets.Array2D(shape=(None, None), dtype="float32"),
+                "land_mask": datasets.Array2D(shape=(None, None), dtype="int8"),
+                "crop_mask": datasets.Array2D(shape=(None, None), dtype="int8"),
+                "irr_mask": datasets.Array2D(shape=(None, None), dtype="int8"),
+                "subirr_mask": datasets.Array2D(shape=(None, None), dtype="int8"),
+                "image_path": datasets.Value("string"),
+                "label_type": datasets.Value("string"),
+                "text_prompt": datasets.Value("string"),
+                "polygon": datasets.Value("string"),
+                "crs": datasets.Value("string"),
+                "split": datasets.Value("string"),
+            })
+        )
+
+    def _split_generators(self, dl_manager):
+        # Download full dataset and split JSON
+        data_dir = dl_manager.download_and_extract("Data/label")
+        split_path = dl_manager.download(self.config.split_file)
+
+        with open(split_path, "r") as f:
+            split_dict = json.load(f)
+
+        def get_file_paths(split_list):
+            return [os.path.join(data_dir, item["h5_path"].replace("Data/label/", "")) for item in split_list]
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": get_file_paths(split_dict["train"])}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"files": get_file_paths(split_dict["test"])}),
+        ]
+
+    def _generate_examples(self, files):
+        for h5_path in files:
+            with h5py.File(h5_path, "r") as f:
+                patch_id = os.path.basename(h5_path).replace(".h5", "")
+                yield patch_id, {
+                    "id": patch_id,
+                    "rgb": f["rgb"][()],
+                    "agri_index": f["agri_index"][()],
+                    "land_mask": f["land_mask"][()],
+                    "crop_mask": f["crop_mask"][()],
+                    "irr_mask": f["irr_mask"][()],
+                    "subirr_mask": f["subirr_mask"][()],
+                    "image_path": f.attrs["image_path"],
+                    "label_type": f.attrs["label_type"],
+                    "text_prompt": f.attrs["text_prompt"],
+                    "polygon": f.attrs["polygon"],
+                    "crs": f.attrs["crs"],
+                    "split": f.attrs["split"],
+                }