Upload SkyScenes.py

SkyScenes.py

@@ -0,0 +1,113 @@
+import collections
+import json
+import os
+
+import datasets
+
+
+# _HOMEPAGE = "
+# _LICENSE = "CC BY 4.0"
+# _CITATION = """\
+# @misc{ buildings-instance-segmentation_dataset,
+#     title = { Buildings Instance Segmentation Dataset },
+#     type = { Open Source Dataset },
+#     author = { Roboflow Universe Projects },
+#     howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation } },
+#     url = { https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation },
+#     journal = { Roboflow Universe },
+#     publisher = { Roboflow },
+#     year = { 2023 },
+#     month = { jan },
+#     note = { visited on 2023-01-18 },
+# }
+# """
+# _CATEGORIES = ['building']
+# _ANNOTATION_FILENAME = "_annotations.coco.json"
+
+
+class SKYSCENESConfig(datasets.BuilderConfig):
+    """Builder Config for satellite-building-segmentation"""
+
+    def __init__(self, data_urls, **kwargs):
+        """
+        BuilderConfig for satellite-building-segmentation.
+        Args:
+          data_urls: `dict`, name to url to download the zip file from.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(SKYSCENESConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+        self.data_urls = data_urls
+
+
+class SKYSCENES(datasets.GeneratorBasedBuilder):
+    """satellite-building-segmentation instance segmentation dataset"""
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        SKYSCENESConfig(
+            name="full",
+            description="Full version of skyscenes dataset.",
+            data_urls={
+                "Images": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town01.tar.gz",
+                "Segment": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town02.tar.gz",
+                "Depth": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town03.tar.gz",
+            },
+        ),
+        SATELLITEBUILDINGSEGMENTATIONConfig(
+            name="mini",
+            description="Mini version of satellite-building-segmentation dataset.",
+            data_urls={
+                "Images": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town01.tar.gz",
+                "Segment": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town02.tar.gz",
+                "Depth": "https://huggingface.co/datasets/hoffman-lab/SkyScenes/blob/main/Images/H_15_P_0/ClearNight/Town03.tar.gz",
+            },
+        )
+    ]
+
+    # def _info(self):
+    #     features = datasets.Features(
+    #         {
+    #             "image_id": datasets.Value("int64"),
+    #             "image": datasets.Image(),
+    #             "width": datasets.Value("int32"),
+    #             "height": datasets.Value("int32"),
+    #             "objects": datasets.Sequence(
+    #                 {
+    #                     "id": datasets.Value("int64"),
+    #                     "area": datasets.Value("int64"),
+    #                     "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
+    #                     "segmentation": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))),
+    #                     "category": datasets.ClassLabel(names=_CATEGORIES),
+    #                 }
+    #             ),
+    #         }
+    #     )
+    #     return datasets.DatasetInfo(
+    #         features=features,
+    #         homepage=_HOMEPAGE,
+    #         citation=_CITATION,
+    #         license=_LICENSE,
+    #     )
+
+    def _split_generators(self, dl_manager):
+        data_files = dl_manager.download_and_extract(self.config.data_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.IMAGES,
+                gen_kwargs={
+                    "folder_dir": data_files["Images"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.SEGMENT,
+                gen_kwargs={
+                    "folder_dir": data_files["Segment"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.DEPTH,
+                gen_kwargs={
+                    "folder_dir": data_files["Depth"],
+                },
+            ),
+]