added another loading Script

LoadingScriptPractice.py

@@ -5,6 +5,8 @@ from datasets import DownloadManager, DatasetInfo
 from datasets.data_files import DataFilesDict
 import os
 import json
+from os.path import dirname, basename
+from pathlib import Path
 
 
 # ここに設定を記入
@@ -12,45 +14,55 @@ _NAME = "mickylan2367/LoadingScriptPractice"
 _EXTENSION = [".png"]
 _REVISION = "main"
 
+# _HOMEPAGE = "https://github.com/fastai/imagenette"
 # プログラムを置く場所が決まったら、ここにホームページURLつける
-_HOMEPAGE = "https://huggingface.co/datasets/mickylan2367/LoadingScriptPractice"
+_HOMEPAGE = "https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps"
 
 _DESCRIPTION = f"""\
 {_NAME} Datasets including spectrogram.png file from Google MusicCaps Datasets!
 Using for Project Learning...
 """
 
-# え...なにこれ(;´･ω･)
-# _IMAGES_DIR = "mickylan2367/images/data/"
-# _REPO = "https://huggingface.co/datasets/frgfm/imagenette/resolve/main/metadata"
+# URLを取得
+
+# class LoadingScriptPracticeConfig(datasets.BuilderConfig):
+#     """BuilderConfig for Imagette."""
+
+#     def __init__(self, data_url, metadata_urls, **kwargs):
+#         """BuilderConfig for Imagette.
+#         Args:
+#           data_url: `string`, url to download the zip file from.
+#           matadata_urls: dictionary with keys 'train' and 'validation' containing the archive metadata URLs
+#           **kwargs: keyword arguments forwarded to super.
+#         """
+#         super(LoadingScriptPracticeConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
+#         self.data_url = data_url
+#         self.metadata_urls = metadata_urls
 
-# 参考になりそうなURL集
-# https://huggingface.co/docs/datasets/v1.1.1/_modules/datasets/utils/download_manager.html
-# https://huggingface.co/docs/datasets/package_reference/builder_classes
-# https://huggingface.co/datasets/animelover/danbooru2022/blob/main/danbooru2022.py
-# https://huggingface.co/datasets/food101/blob/main/food101.py
-# https://huggingface.co/docs/datasets/about_dataset_load
-# https://huggingface.co/datasets/frgfm/imagenette/blob/main/imagenette.py
-# https://huggingface.co/docs/datasets/v1.2.1/add_dataset.html
-# DatasetInfo : https://huggingface.co/docs/datasets/package_reference/main_classes
 
-# 使用したデータセット（クラスラベル）
-# https://huggingface.co/datasets/marsyas/gtzan
 
 class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
 
     # データのサブセットはここで用意
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name="MusicCaps data 0_3",
+            name="train",
             description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
+            # data_url = train_data_url["train"][0],
+            # metadata_urls = {
+            #     "train" : train_metadata_paths["train"][0]
+            # }
         ),
 
         # splits (dict, optional) — The mapping between split name and metadata.
-        # LoadingScriptPracticeConfig(
-        #     name="MusicCaps data ",
-        #     description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
-        # )
+        datasets.BuilderConfig(
+            name="test",
+            description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
+            # data_url = test_data_url["test"][0],
+            # metadata_urls={
+            #     "test" : test_metadata_paths["test"][0]
+            # }
+        )
     ]
 
     def _info(self) -> DatasetInfo:
@@ -89,28 +101,41 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
         # huggingfaceのディレクトリからデータを取ってくる
         hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
 
-        split_metadata_paths = DataFilesDict.from_hf_repo(
+        metadata_urls = DataFilesDict.from_hf_repo(
             {datasets.Split.TRAIN: ["**"]},
             dataset_info=hfh_dataset_info,
             allowed_extensions=["jsonl", ".jsonl"],
         )
-        
+
         # **.zipのURLをDict型として取得？
-        data_path = DataFilesDict.from_hf_repo(
+        data_urls = DataFilesDict.from_hf_repo(
             {datasets.Split.TRAIN: ["**"]},
             dataset_info=hfh_dataset_info,
             allowed_extensions=["zip", ".zip"],
         )
+
+        data_paths = dict()
+        for path in data_path["train"]:
+            dname = dirname(path)
+            folder = basename(Path(dname))
+            data_paths[folder] = path
+
+        metadata_paths = dict()
+        for path in data_path["train"]:
+            dname = dirname(path)
+            folder = basename(Path(dname))
+            metadata_paths[folder] = path
+
         
         gs = []
-        for split, files in data_path.items():
+        for split, files in data_paths.items():
             '''
             split : "train" or "test" or "val"
             files : zip files
             '''
             # リポジトリから��ウンロードしてとりあえずキャッシュしたURLリストを取得
-            split_metadata_path = dl_manager.download_and_extract(split_metadata_paths[split][0])
-            downloaded_files_path = dl_manager.download(files[0]) 
+            metadata_path = dl_manager.download_and_extract(metadata_paths[split])
+            downloaded_files_path = dl_manager.download(files) 
             
             # 元のコードではzipファイルの中身を"filepath"としてそのまま_generate_exampleに引き渡している？
             gs.append(
@@ -118,7 +143,7 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
                   name = split, 
                   gen_kwargs={
                      "images" : dl_manager.iter_archive(downloaded_files_path), 
-                     "metadata_path": split_metadata_path
+                     "metadata_path": metadata_path
                      }
                   )
             )

try.py

@@ -1,183 +0,0 @@
-
-import datasets
-from huggingface_hub import HfApi
-from datasets import DownloadManager, DatasetInfo
-from datasets.data_files import DataFilesDict
-import os
-import json
-from os.path import dirname, basename
-from pathlib import Path
-
-
-# ここに設定を記入
-_NAME = "mickylan2367/LoadingScriptPractice"
-_EXTENSION = [".png"]
-_REVISION = "main"
-
-# _HOMEPAGE = "https://github.com/fastai/imagenette"
-# プログラムを置く場所が決まったら、ここにホームページURLつける
-_HOMEPAGE = "https://huggingface.co/datasets/mickylan2367/spectrogram_musicCaps"
-
-_DESCRIPTION = f"""\
-{_NAME} Datasets including spectrogram.png file from Google MusicCaps Datasets!
-Using for Project Learning...
-"""
-
-# URLを取得
-
-# class LoadingScriptPracticeConfig(datasets.BuilderConfig):
-#     """BuilderConfig for Imagette."""
-
-#     def __init__(self, data_url, metadata_urls, **kwargs):
-#         """BuilderConfig for Imagette.
-#         Args:
-#           data_url: `string`, url to download the zip file from.
-#           matadata_urls: dictionary with keys 'train' and 'validation' containing the archive metadata URLs
-#           **kwargs: keyword arguments forwarded to super.
-#         """
-#         super(LoadingScriptPracticeConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
-#         self.data_url = data_url
-#         self.metadata_urls = metadata_urls
-
-
-
-class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
-
-    # データのサブセットはここで用意
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="train",
-            description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
-            # data_url = train_data_url["train"][0],
-            # metadata_urls = {
-            #     "train" : train_metadata_paths["train"][0]
-            # }
-        ),
-
-        # splits (dict, optional) — The mapping between split name and metadata.
-        datasets.BuilderConfig(
-            name="test",
-            description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
-            # data_url = test_data_url["test"][0],
-            # metadata_urls={
-            #     "test" : test_metadata_paths["test"][0]
-            # }
-        )
-    ]
-
-    def _info(self) -> DatasetInfo:
-      return datasets.DatasetInfo(
-          description = self.config.description,
-          features=datasets.Features(
-              {
-                  "image": datasets.Image(),
-                  "caption": datasets.Value("string"),
-                  "data_idx": datasets.Value("int32"),
-                  "number" : datasets.Value("int32"),
-                  "label" : datasets.ClassLabel(
-                        names=[
-                            "blues",
-                            "classical",
-                            "country",
-                            "disco",
-                            "hiphop",
-                            "metal",
-                            "pop",
-                            "reggae",
-                            "rock",
-                            "jazz"
-                        ]
-                  )
-              }
-          ),
-          supervised_keys=("image", "caption"),
-          homepage=_HOMEPAGE,
-          citation= "",
-          # license=_LICENSE,
-          # task_templates=[ImageClassification(image_column="image", label_column="label")],
-      )
-
-    def _split_generators(self, dl_manager: DownloadManager):
-        # huggingfaceのディレクトリからデータを取ってくる
-        hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
-
-        metadata_urls = DataFilesDict.from_hf_repo(
-            {datasets.Split.TRAIN: ["**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["jsonl", ".jsonl"],
-        )
-
-        # **.zipのURLをDict型として取得？
-        data_urls = DataFilesDict.from_hf_repo(
-            {datasets.Split.TRAIN: ["**"]},
-            dataset_info=hfh_dataset_info,
-            allowed_extensions=["zip", ".zip"],
-        )
-
-        data_paths = dict()
-        for path in data_path["train"]:
-            dname = dirname(path)
-            folder = basename(Path(dname))
-            data_paths[folder] = path
-
-        metadata_paths = dict()
-        for path in data_path["train"]:
-            dname = dirname(path)
-            folder = basename(Path(dname))
-            metadata_paths[folder] = path
-
-        
-        gs = []
-        for split, files in data_paths.items():
-            '''
-            split : "train" or "test" or "val"
-            files : zip files
-            '''
-            # リポジトリからダウンロードしてとりあえずキャッシュしたURLリストを取得
-            metadata_path = dl_manager.download_and_extract(metadata_paths[split])
-            downloaded_files_path = dl_manager.download(files) 
-            
-            # 元のコードではzipファイルの中身を"filepath"としてそのまま_generate_exampleに引き渡している？
-            gs.append(
-               datasets.SplitGenerator(
-                  name = split, 
-                  gen_kwargs={
-                     "images" : dl_manager.iter_archive(downloaded_files_path), 
-                     "metadata_path": metadata_path
-                     }
-                  )
-            )
-        return gs
-
-    def _generate_examples(self, images, metadata_path):
-        """Generate images and captions for splits."""
-        # with open(metadata_path, encoding="utf-8") as f:
-        #     files_to_keep = set(f.read().split("\n"))
-        file_list = list()
-        caption_list = list()
-        dataIDX_list = list()
-        num_list = list()
-        label_list = list()
-
-        with open(metadata_path) as fin:
-            for line in fin:
-                data =  json.loads(line)
-                file_list.append(data["file_name"])
-                caption_list.append(data["caption"])
-                dataIDX_list.append(data["data_idx"])
-                num_list.append(data["number"])
-                label_list.append(data["label"])
-
-        for idx, (file_path, file_obj) in enumerate(images):
-            yield file_path, {
-                "image": {
-                    "path": file_path, 
-                    "bytes": file_obj.read()
-                },
-                "caption" : caption_list[idx],
-                "data_idx" : dataIDX_list[idx],
-                "number" : num_list[idx],
-                "label": label_list[idx]
-            }
-
-