changed loading script

GraySpectrogram2.py → GraySpectrogram.py

@@ -10,7 +10,7 @@ from pathlib import Path
 
 
 # ここに設定を記入
-_NAME = "mickylan2367/LoadingScriptPractice"
+_NAME = "mickylan2367/GraySpectrogram"
 _EXTENSION = [".png"]
 _REVISION = "main"
 
@@ -35,17 +35,13 @@ Using for Project Learning...
 
 
 
-class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
+class GraySpectrogram2(datasets.GeneratorBasedBuilder):
 
     # データのサブセットはここで用意
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
             name="train",
             description=_DESCRIPTION,
-            # data_url = train_data_url["train"][0],
-            # metadata_urls = {
-            #     "train" : train_metadata_paths["train"][0]
-            # }
         )
     ]
 
@@ -85,54 +81,82 @@ 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)
 
+        # メタデータであるjsonlファイルのURLを取得
         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？
+        # 辞書型にしてURLを格納し直す <- 正しい辞書型にできていたら、必要ないかも
+        metadata_paths = dict()
+        for path in metadata_urls["train"]:
+            dname = dirname(path)
+            folder = basename(Path(dname))
+            # fname = basename(path)
+            metadata_paths[folder] = path
+
+        # 画像データは**.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()
+        data_url = dict()
+        train_data_url = list()
+        test_data_url = list()
         for path in data_urls["train"]:
             dname = dirname(path)
             folder = basename(Path(dname))
-            data_paths[folder] = path
-
-        metadata_paths = dict()
-        for path in metadata_urls["train"]:
-            dname = dirname(path)
-            folder = basename(Path(dname))
-            metadata_paths[folder] = path
-
+            # 辞書型
+            if folder=="train":
+                train_data_url.append(path)
+            if folder == "test":
+                test_data_url.append(path)
+
+        data_url["train"] = train_data_url
+        data_url["test"] = test_data_url
+
+        # iteration
+        iter_archive = dict()
+        for split, files in data_url.items():
+            file_name_obj = list()
+            for file_ in files:
+                downloaded_files_path = dl_manager.download(file_)
+                for file_obj in dl_manager.iter_archive(downloaded_files_path):
+                    # print(file_obj)
+                    if file_obj[0].startswith('content/'):
+                        fname = basename(file_obj[0])
+                        file_obj = (fname, file_obj[1])
+                        file_name_obj.append(file_obj)
+                        # print(file_obj)
+                    else:
+                        file_name_obj.append(file_obj)
+                        # print(file_obj)
+            iter_archive[split] = file_name_obj
         
         gs = []
-        for split, files in data_paths.items():
+        for split, files in iter_archive.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
-                     }
-                  )
+                datasets.SplitGenerator(
+                    name = split,
+                    gen_kwargs = {
+                        "images" : iter(iter_archive[split]),
+                        "metadata_path": metadata_path # メタデータパスを渡す
+                    }
+                )
             )
         return gs
 
+    
     def _generate_examples(self, images, metadata_path):
         """Generate images and captions for splits."""
         # with open(metadata_path, encoding="utf-8") as f:
@@ -163,5 +187,3 @@ class LoadingScriptPractice(datasets.GeneratorBasedBuilder):
                 "number" : num_list[idx],
                 "label": label_list[idx]
             }
-
-

data/test/test_0002.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4b799a2c436036f92650f195914f8fccf9fc6fb81378438f0f94a97828cff70d
+size 95043607

data/test/test_0003.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:145c674bf0d7f296b96a9795e406d870e465eb3269f12c6ab7e98db3e9ea8015
+size 53560142

data/train/train_0002.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38feda20bf89720100fd388ed7f78214177a958a4f6214c8460bc03bb21e3142
+size 71536214

data/train/train_0003.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4391664cb29e687e63d591f5b9350883352ec0db0f32f1e8e0c780b463ef1532
+size 73587192