Refactor Meter2800 dataset class and improve example generation logic

meter2800.py

@@ -1,6 +1,6 @@
-from pathlib import Path
 import datasets
 import pandas as pd
+from pathlib import Path
 
 _CITATION = """\
 @misc{meter2800_dataset,
@@ -14,8 +14,7 @@ _CITATION = """\
 
 _DESCRIPTION = """\
 Meter2800 is a dataset of 2,800 music audio samples for automatic meter classification.
-Each audio file is annotated with a primary meter class label (e.g., 'two', 'three', 'four') 
-and an alternative meter (numerical, e.g., 2, 3, 4, 6). 
+Each audio file is annotated with a primary meter class label and an alternative meter.
 It is split into training, validation, and test sets, each available in two class configurations:
 2-class and 4-class. All audio is 16-bit WAV format.
 """
@@ -23,50 +22,35 @@ It is split into training, validation, and test sets, each available in two clas
 _HOMEPAGE = "https://huggingface.co/datasets/pianistprogrammer/Meter2800"
 _LICENSE = "mit"
 
-# Define the labels - adjust these based on your actual data
-LABELS_4 = ["three", "four", "five", "seven"]
-LABELS_2 = ["simple", "complex"]  # or whatever your 2-class grouping actually is
-
-class Meter2800Config(datasets.BuilderConfig):
-    """BuilderConfig for Meter2800."""
-    def __init__(self, name, **kwargs):
-        super(Meter2800Config, self).__init__(
-            name=name,
-            version=datasets.Version("1.0.0"),
-            **kwargs
-        )
-
 class Meter2800(datasets.GeneratorBasedBuilder):
-    """Meter2800 dataset."""
+    """Meter2800 dataset for music meter classification."""
+
+    VERSION = datasets.Version("1.0.0")
     
     BUILDER_CONFIGS = [
-        Meter2800Config(
+        datasets.BuilderConfig(
             name="4_classes",
-            description="4-class meter classification"
+            version=VERSION,
+            description="4-class meter classification",
         ),
-        Meter2800Config(
-            name="2_classes", 
-            description="2-class meter classification"
+        datasets.BuilderConfig(
+            name="2_classes",
+            version=VERSION,
+            description="2-class meter classification",
         ),
     ]
-    
+
     DEFAULT_CONFIG_NAME = "4_classes"
 
     def _info(self):
-        if self.config.name == "4_classes":
-            label_names = LABELS_4
-        elif self.config.name == "2_classes":
-            label_names = LABELS_2
-        else:
-            # Fallback - shouldn't happen with proper configs
-            label_names = LABELS_4
-            
+        # We'll determine the labels dynamically from the CSV files
+        # For now, use a generic ClassLabel that will be updated later
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=datasets.Features({
                 "filename": datasets.Value("string"),
                 "audio": datasets.Audio(sampling_rate=None),
-                "label": datasets.ClassLabel(names=label_names),
+                "label": datasets.Value("string"),  # We'll convert to ClassLabel later
                 "meter": datasets.Value("string"),
                 "alt_meter": datasets.Value("string"),
             }),
@@ -77,45 +61,55 @@ class Meter2800(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        # Get the data directory
-        data_dir = dl_manager.download_and_extract("")
+        """Returns SplitGenerators."""
+        
+        # The files should be in the root of the repo
+        config_suffix = self.config.name
         
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "csv_file": f"{data_dir}/data_train_{self.config.name}.csv",
-                    "data_dir": data_dir
+                    "csv_file": f"data_train_{config_suffix}.csv",
+                    "split": "train",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "csv_file": f"{data_dir}/data_val_{self.config.name}.csv",
-                    "data_dir": data_dir
+                    "csv_file": f"data_val_{config_suffix}.csv",
+                    "split": "validation",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "csv_file": f"{data_dir}/data_test_{self.config.name}.csv",
-                    "data_dir": data_dir
+                    "csv_file": f"data_test_{config_suffix}.csv",
+                    "split": "test",
                 },
             ),
         ]
 
-    def _generate_examples(self, csv_file, data_dir):
+    def _generate_examples(self, csv_file, split):
+        """Yields examples."""
+        
+        # Read CSV directly - the file should be available in the repo
+        df = pd.read_csv(csv_file)
+        
+        # Read CSV
         df = pd.read_csv(csv_file)
-        df = df.dropna(subset=["filename", "label", "meter"]).reset_index(drop=True)
+        df = df.dropna(subset=["filename", "label"]).reset_index(drop=True)
 
         for idx, row in df.iterrows():
-            # Construct the full audio path
-            audio_path = f"{data_dir}/{row['filename']}"
+            # The audio files should be in subdirectories
+            audio_file = row["filename"]
+            if not audio_file.startswith("/"):
+                audio_file = "/" + audio_file
             
             yield idx, {
                 "filename": row["filename"],
-                "audio": audio_path,
-                "label": row["label"],
-                "meter": str(row["meter"]),
-                "alt_meter": str(row.get("alt_meter", row["meter"])),
+                "audio": audio_file.lstrip("/"),  # Remove leading slash for HF
+                "label": str(row["label"]),
+                "meter": str(row.get("meter", "")),
+                "alt_meter": str(row.get("alt_meter", row.get("meter", ""))),
             }