Create MapReader_Data_SIGSPATIAL_2022.py

MapReader_Data_SIGSPATIAL_2022.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""TODO"""
+
+import csv
+import os
+
+import datasets
+from PIL import Image
+
+_CITATION = """\
+@dataset{kasra_hosseini_2022_7147906,
+  author       = {Kasra Hosseini and
+                  Daniel C.S. Wilson and
+                  Kaspar Beelen and
+                  Katherine McDonough},
+  title        = {MapReader_Data_SIGSPATIAL_2022},
+  month        = oct,
+  year         = 2022,
+  publisher    = {Zenodo},
+  version      = {v0.3.3},
+  doi          = {10.5281/zenodo.7147906},
+  url          = {https://doi.org/10.5281/zenodo.7147906}
+}
+"""
+
+_DESCRIPTION = """\
+TODO"""
+
+_HOMEPAGE = "https://doi.org/10.5281/zenodo.3366686"
+_LICENSE = "Creative Commons Attribution Non Commercial Share Alike 4.0 International"
+
+_URL = "https://zenodo.org/record/7147906/files/MapReader_Data_SIGSPATIAL_2022.zip?download=1"
+
+
+class RailspaceData(datasets.GeneratorBasedBuilder):
+    """National Library of Scotland Railspace dataset."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "label": datasets.ClassLabel(
+                    names=[
+                        "no building or railspace",
+                        "railspace",
+                        "building",
+                        "railspace and non railspace building",
+                    ]
+                ),  # Labels: 0: no [building or railspace]; 1: railspace; 2: building; and 3: railspace and [non railspace] building.
+                "map_sheet": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"data": data, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"data": data, "split": "valid"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"data": data, "split": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, data, split):
+        with open(
+            os.path.join(
+                data, f"MapReader_Data_SIGSPATIAL_2022/annotations/{split}.csv"
+            ),
+            "r",
+        ) as f:
+            reader = csv.DictReader(f)
+            for id_, row in enumerate(reader):
+                label = row["label"]
+                map_sheet = row["image_id"].split("#")[1]
+                image_file = os.path.join(
+                    data,
+                    f"MapReader_Data_SIGSPATIAL_2022/annotations/{row['image_id']}",
+                )
+                image = Image.open(image_file)
+                yield id_, {"image": image, "label": label, "map_sheet": map_sheet}