Convert dataset to Parquet (#2)

- Convert dataset to Parquet (8cccce533b3f7c54ec2686e6f186ba6bcd931a6b)
- Delete loading script (05c785c6f7d23f2482427b8166495e58a48df7e2)
- Delete data file (0f157d87a8c1a51deff6ab27753e60a68593314c)
- Delete data file (b30a9cee5255b582415cf172dfa141ac74547dfd)
- Delete data file (ab97d677fce8920822f23ebeb5980c9f8f6dbe7c)
- Delete data file (5b7dfed1a0c9cd0f692459bd1952dd974df64267)


Co-authored-by: Albert Villanova <[email protected]>

BA_Datensatz_V2.py

@@ -1,82 +0,0 @@
-import datasets
-import csv
-import json
-import os
-import csv
-
-# Defining Access
-_DATA_URL = "https://huggingface.co/datasets/LennyBijan/BA_Datensatz_V2/resolve/main/data"
-
-
-class BA_Datensatz_V2(datasets.GeneratorBasedBuilder):
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description="German Dataset that focuses on juristical data",
-            features=datasets.Features({
-                "clip_id": datasets.Value("string"),
-                "path": datasets.Value("string"),
-                "audio": datasets.Audio(sampling_rate=16_000),
-                "sentence": datasets.Value("string"),
-                "split": datasets.Value("string")
-            }),
-            supervised_keys=None,
-        )
-
-    def _split_generators(self, dl_manager):
-        dl_manager.download_config.ignore_url_params = True
-
-        audio_path = {}
-        local_extracted_archive = {}
-        metadata_path = {}
-        split_type = {"train": datasets.Split.TRAIN, "test": datasets.Split.TEST}
-        for split in split_type:
-            audio_path[split] = dl_manager.download(f"{_DATA_URL}/audio_{split}.tgz")
-            local_extracted_archive[split] = dl_manager.extract(audio_path[split]) if not dl_manager.is_streaming else None
-            metadata_path[split] = dl_manager.download_and_extract(f"{_DATA_URL}/metadata_{split}.csv.gz")
-        path_to_clips = "BA_Datensatz_V2"
-
-        return [
-            datasets.SplitGenerator(
-                name=split_type[split],
-                gen_kwargs={
-                    "local_extracted_archive": local_extracted_archive[split],
-                    "audio_files": dl_manager.iter_archive(audio_path[split]),
-                    "metadata_path": dl_manager.download_and_extract(metadata_path[split]),
-                    "path_to_clips": path_to_clips,
-                    "split": split  # pass the split name to _generate_examples
-                },
-            ) for split in split_type
-        ] 
-
-    def _generate_examples(self, audio_files, metadata_path, path_to_clips, local_extracted_archive, split):
-        metadata = {}
-        # Open and read the metadata CSV file.
-        with open(metadata_path, "r", encoding="utf-8") as f:
-            reader = csv.reader(f)
-            for row in reader:
-                filename, sentence = row
-                clip_id = filename.split('_')[0]
-                # Append the split name dynamically to the path_to_clips.
-                path = os.path.join(path_to_clips, split +"/wav/"+ clip_id, filename)
-                metadata[path] = {
-                    "clip_id": clip_id,
-                    "sentence": sentence,
-                    "path": path,
-                }
-        id_ = 0
-        for path, file_content in audio_files: # No need to adjust the path if no local extraction.
-            if path in metadata:
-                result = dict(metadata[path])
-                path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
-                audio_data = {"path": path, "bytes": file_content.read()}
-                result["audio"] = audio_data
-                result["path"] = path
-                yield id_, result
-                id_ += 1
-            else:
-                print(f"No metadata entry for {path}")
-
-
-
-

README.md

@@ -21,20 +21,22 @@ dataset_info:
         sampling_rate: 16000
   - name: sentence
     dtype: string
+  - name: split
+    dtype: string
   splits:
   - name: train
-    num_bytes: 1040277177.0
+    num_bytes: 1043053050.066
     num_examples: 4441
   - name: test
-    num_bytes: 349166136.0
+    num_bytes: 349087555.272
     num_examples: 1483
-  download_size: 1388336650
-  dataset_size: 1389443313.0
-  configs:
-  - config_name: default
-    data_files:
-    - split: train
-      path: "data/metadata_train.csv.gz"
-    - split: test
-      path: "data/metadata_test.csv.gz"
+  download_size: 1389079147
+  dataset_size: 1392140605.338
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
 ---

data/audio_test.tgz

@@ -1,3 +0,0 @@
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-size 300579710

data/audio_train.tgz

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data/metadata_test.csv.gz

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data/metadata_train.csv.gz

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data/test-00000-of-00001.parquet

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