change repository contructure

LoadingScriptPractice.py

@@ -12,9 +12,8 @@ _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"
+_HOMEPAGE = "https://huggingface.co/datasets/mickylan2367/LoadingScriptPractice"
 
 _DESCRIPTION = f"""\
 {_NAME} Datasets including spectrogram.png file from Google MusicCaps Datasets!
@@ -27,50 +26,61 @@ Using for Project Learning...
 
 # 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
 
-
-class LoadingScriptPracticeConfig(datasets.BuilderConfig):
-    """Builder Config for spectrogram_MusicCaps"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig
-        Args:
-          data_url: `string`, url to download the zip file from.
-          metadata_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
+# 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 = [
-        LoadingScriptPracticeConfig(
+        datasets.BuilderConfig(
             name="MusicCaps data 0_3",
             description="this Datasets is personal practice for using loadingScript. Data is from Google/MusicCaps",
-        )
+        ),
+
+        # 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",
+        # )
     ]
 
-    def _info(self):
+    def _info(self) -> DatasetInfo:
       return datasets.DatasetInfo(
-          description=_DESCRIPTION,
+          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.Value("string")
+                  "label" : datasets.ClassLabel(
+                        names=[
+                            "blues",
+                            "classical",
+                            "country",
+                            "disco",
+                            "hiphop",
+                            "metal",
+                            "pop",
+                            "reggae",
+                            "rock",
+                            "jazz"
+                        ]
+                  )
               }
           ),
-          supervised_keys=("image", "caption", "data_idx", "number", "label"),
+          supervised_keys=("image", "caption"),
           homepage=_HOMEPAGE,
-          # citation=_CITATION,
+          citation= "",
           # license=_LICENSE,
           # task_templates=[ImageClassification(image_column="image", label_column="label")],
       )
@@ -99,8 +109,8 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
             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
-            split_metadata_path = split_metadata_paths[split][0]
-            downloaded_files_path = dl_manager.download_and_extract(files) 
+            split_metadata_path = dl_manager.download_and_extract(split_metadata_paths[split][0])
+            downloaded_files_path = dl_manager.download(files[0]) 
             
             # 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(
@@ -111,10 +121,10 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
                      "metadata_path": split_metadata_path
                      }
                   )
-            ) 
+            )
         return gs
 
-    def _generate_examples(self, images, metadata_path, dl_manager:DownloadManager):
+    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"))
@@ -124,7 +134,7 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
         num_list = list()
         label_list = list()
 
-        with open(dl_manager.download_and_extract(metadata_path)) as fin:
+        with open(metadata_path) as fin:
             for line in fin:
                 data =  json.loads(line)
                 file_list.append(data["file_name"])

data/test/data-0000.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:51f3fc0c7e3b8d072c84e40b8430d307372915e56f36e1d4c78fd8bd14d2dae2
+size 440052

data/test/metadata.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7249fa1e7e947587c4aff6ba30754d65b6e181f3b8d1aac6a11337322fb383b6
+size 2592

try.py

@@ -0,0 +1,191 @@
+
+import datasets
+from huggingface_hub import HfApi
+from datasets import DownloadManager, DatasetInfo
+from datasets.data_files import DataFilesDict
+import os
+import json
+
+
+# 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)
+
+        train_metadata_paths = DataFilesDict.from_hf_repo(
+            {datasets.Split.TRAIN: ["**"]},
+            dataset_info=hfh_dataset_info,
+            allowed_extensions=["jsonl", ".jsonl"],
+        )
+
+        test_metadata_paths = DataFilesDict.from_hf_repo(
+            {datasets.Split.TEST: ["**"]},
+            dataset_info=hfh_dataset_info,
+            allowed_extensions=["jsonl", ".jsonl"],
+        )
+
+        # **.zipのURLをDict型として取得？
+        train_data_url = DataFilesDict.from_hf_repo(
+            {datasets.Split.TRAIN: ["**"]},
+            dataset_info=hfh_dataset_info,
+            allowed_extensions=["zip", ".zip"],
+        )
+
+        test_data_url = DataFilesDict.from_hf_repo(
+            {datasets.Split.test: ["**"]},
+            dataset_info=hfh_dataset_info,
+            allowed_extensions=["zip", ".zip"],
+        )
+
+        # 扱いやすいように再構成
+        data_path = {
+            "train" : train_data_url["train"][0],
+            "test" : test_data_url["test"][0]
+        }
+
+        split_metadata_paths= {
+            "train" : train_metadata_paths["train"][0],
+            "test" : test_metadata_paths["test"][0]
+        }
+        
+        gs = []
+        for split, files in data_path.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
+            split_metadata_path = dl_manager.download_and_extract(split_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": split_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]
+            }
+
+