modified config.splits form url

dcase23-task2-enriched.py

@@ -3,6 +3,7 @@ import datasets
 import datasets.info
 import pandas as pd
 from pathlib import Path
+from renumics import spotlight
 from datasets import load_dataset
 from typing import Iterable, Dict, Optional, Union, List
 
@@ -49,8 +50,16 @@ DATA_URLS = {
         "test": "data/dev_test.tar.gz",
         "metadata": "data/dev_metadata.csv",
     },
-    "add": None,
-    "eval": None,
+    "add":  {
+        "train": "data/add_train.tar.gz",
+        "test": "data/add_test.tar.gz",
+        "metadata": "data/add_metadata.csv",
+    },
+    "eval": {
+        "train": "data/eval_train.tar.gz",
+        "test": "data/eval_test.tar.gz",
+        "metadata": "data/eval_metadata.csv",
+    },
 }
 
 STATS = {
@@ -105,7 +114,7 @@ class DCASE2023Task2DatasetConfig(datasets.BuilderConfig):
             f"Dataset for the DCASE 2023 Challenge Task 2 'First-Shot Unsupervised Anomalous Sound Detection "
             f"for Machine Condition Monitoring'. released on {self.release_date}. Original data available under"
             f"{self.homepage}. "
-            f"SPLIT: {name}."
+            f"CONFIG: {name}."
         )
         super(DCASE2023Task2DatasetConfig, self).__init__(
             name=name,
@@ -113,6 +122,27 @@ class DCASE2023Task2DatasetConfig(datasets.BuilderConfig):
             description=description,
         )
 
+    def to_spotlight(self, data: Union[pd.DataFrame, datasets.Dataset]) -> pd.DataFrame:
+        if type(data) == datasets.Dataset:
+            df = data.to_pandas()
+            df["split"] = data.split
+            df["config"] = data.config_name
+
+            class_names = data.features["class"].names
+            df["class_name"] = df["class"].apply(lambda x: class_names[x])
+        elif type(data) == pd.DataFrame:
+            df = data
+        else:
+            raise TypeError("type(data) not in Union[pd.DataFrame, datasets.Dataset]")
+
+        df["file_path"] = df["path"]
+        df.rename(columns=self._rename, inplace=True)
+
+        return df.copy()
+
+    def get_layout(self):
+        return self._layout
+
 
 class DCASE2023Task2Dataset(datasets.GeneratorBasedBuilder):
     """Dataset for the DCASE 2023 Challenge Task 2 "First-Shot Unsupervised Anomalous Sound Detection
@@ -214,3 +244,8 @@ class DCASE2023Task2Dataset(datasets.GeneratorBasedBuilder):
                 result["path"] = path
                 yield id_, {**result, "audio": audio}
                 id_ += 1
+
+
+if __name__ == "__main__":
+    ds = load_dataset("dcase23-task2-enriched.py", "dev", split="train", streaming=True)
+