add parquet

README.md

@@ -3,18 +3,11 @@ configs:
   - config_name: default
     data_files:
       - split: train
-        path: "data/train/metadata.csv"
+        path: "data/train.parquet"
       - split: validation
-        path: "data/validation/metadata.csv"
+        path: "data/validation.parquet"
       - split: test
-        path: "data/test/metadata.csv"
-    features:
-      image:
-        dtype: image
-        description: High-resolution input images of urban environments.
-      mask:
-        dtype: image
-        description: Binary segmentation masks corresponding to each input image.
+        path: "data/test.parquet"
 ---
 
 # Urban Climate Dataset

data/{test/metadata.csv → test.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f03eb39a936bb2da28c2fbb14a1b13d670fbf65cc08bf519fd52b22e9e0e1539
-size 63872
+oid sha256:f805830c1a43bdebaff04ef67fa43f1b9a5c1217300459aaf8b54ffda34c7f64
+size 785318981

data/{validation/metadata.csv → train.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d04ab420a459f0f6c61021686ff949b683e73fd773769dae04d069c42e99d5cd
-size 62636
+oid sha256:cdf6ed4e2a5a7b71e37f2d3361474795aab68feb1411fba4dbdf8efd10a81d4f
+size 10868106153

data/{train/metadata.csv → validation.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b8d3d19baf725ff7132bdc82ee7fb38fae31530328a77a9455b9cefd7453ce7e
-size 317378
+oid sha256:3b2397d994e8ae12dc2153adf80c8df48a14e1742b5a25395fc284de8fa44c6f
+size 1992539392

dataset.py

@@ -1,61 +0,0 @@
-import os
-import pandas as pd
-from datasets import GeneratorBasedBuilder, DatasetInfo, Features, Image, Value, SplitGenerator
-
-class UrbanClimateDataset(GeneratorBasedBuilder):
-    """Urban Climate Dataset for building detection."""
-
-    VERSION = "1.0.0"
-
-    def _info(self):
-        return DatasetInfo(
-            description="Dataset for building detection in urban environments using image segmentation.",
-            features=Features({
-                "file_name": Value("string"),
-                "image": Image(),
-                "mask": Image(),
-                "type": Value("string"),
-            }),
-            supervised_keys=None,
-            homepage="https://huggingface.co/datasets/nave1616/urban_climate_dataset",
-            license="CC BY-SA 4.0",
-            citation="""@article{your_citation}"""
-        )
-
-    def _split_generators(self, dl_manager):
-        """Specify data splits."""
-        base_path = dl_manager.download_and_extract(self.config.data_dir)
-        
-        return [
-            SplitGenerator(
-                name="train",
-                gen_kwargs={"files_dir": os.path.join(base_path, "train")},
-            ),
-            SplitGenerator(
-                name="validation",
-                gen_kwargs={"files_dir": os.path.join(base_path, "validation")},
-            ),
-            SplitGenerator(
-                name="test",
-                gen_kwargs={"files_dir": os.path.join(base_path, "test")},
-            ),
-        ]
-
-    def _generate_examples(self, files_dir):
-        """Generate examples from metadata CSV files."""
-        metadata_path = os.path.join(files_dir, 'metadata.csv')
-        df = pd.read_csv(metadata_path)
-        for idx, row in df.iterrows():
-            image_path = os.path.join(files_dir, row["file_name"])
-            # Assume that mask images are in the same directory and have the same name with a different prefix
-            if row['type'] == 'image':
-                mask_path = image_path.replace('image', 'mask')  # Replace to get the corresponding mask path
-            else:
-                mask_path = image_path
-
-            yield idx, {
-                "file_name": row["file_name"],
-                "image": image_path if row['type'] == 'image' else None,
-                "mask": mask_path if row['type'] == 'mask' else None,
-                "type": row["type"],
-            }