Rename trainimgs.py to test.py

test.py

@@ -0,0 +1,53 @@
+import os
+import datasets
+import urllib.request
+import csv
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {diffusion train set},
+}
+"""
+
+_DESCRIPTION = """\
+This is a dataset that image data and caption txt
+"""
+_HOMEPAGE = ""
+
+_LICENSE = ""
+
+_URL = "./"
+
+_URLS = {        
+            "train": "/content/drive/MyDrive/",
+            "reg": "/content/drive/MyDrive/",
+            }
+
+
+train = open("/content/drive/MyDrive/train_dataset.csv", "r")
+train_reader = csv.DictReader(train)
+# if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
+#     os.makedirs(outpath)
+for row in train_reader:
+    class_name = f"{row['Class_name']}"
+    file_name = f"{row['file_name']}"
+    url = f"{row['file_id']}"
+    path = os.path.join('./img',class_name,file_name)
+    folder = os.path.join('./img',class_name)
+    if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
+        os.makedirs(folder)
+    urllib.request.urlretrieve(url, path)
+
+reg = open("/content/drive/MyDrive/reg_dataset.csv", "r")
+reg_reader = csv.DictReader(reg)
+# if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
+#     os.makedirs(outpath)
+for row in reg_reader:
+    class_name = f"{row['Class_name']}"
+    file_name = f"{row['file_name']}"
+    url = f"{row['file_id']}"
+    path = os.path.join('./reg',class_name,file_name)
+    folder = os.path.join('./reg',class_name)
+    if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
+        os.makedirs(folder)
+    urllib.request.urlretrieve(url, path)

trainimgs.py

@@ -1,133 +0,0 @@
-import os
-import datasets
-import urllib.request
-import csv
-
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {diffusion train set},
-}
-"""
-
-_DESCRIPTION = """\
-This is a dataset that image data and caption txt
-"""
-_HOMEPAGE = ""
-
-_LICENSE = ""
-
-_URL = "./"
-
-_URLS = {        
-            "train": "/content/drive/MyDrive/",
-            "reg": "/content/drive/MyDrive/",
-            }
-
-class imgdataset(datasets.GeneratorBasedBuilder):
-    """"""
-    VERSION = datasets.Version("1.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="train", version=VERSION),
-        datasets.BuilderConfig(name="reg", version=VERSION),
-    ]
-
-
-    def _info(self):
-        if self.config.name == "train":  
-            features = datasets.Features(
-                {
-                    "Class_name": datasets.Value("string"),
-                    "file_name": datasets.Value("string"),
-                    "file_id": datasets.Value("string")
-
-                }
-            )
-        else:  
-            features = datasets.Features(
-                {
-                    "Class_name": datasets.Value("string"),
-                    "file_name": datasets.Value("string"),
-                    "file_id": datasets.Value("string")
-
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features, 
-        )
-    
-    def _split_generators(self, dl_manager):
-        """This function returns the examples in the raw (text) form."""
-        
-        # urls = _URLS[self.config.name]
-        # data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join("/content/drive/MyDrive/", "train_dataset.csv"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join("/content/drive/MyDrive/", "reg_dataset.csv"),
-                    "split": "reg",
-                },
-            ),
-       ]
-    def _download_image(self, dl_manager):
-
-
-        train = open("/content/drive/MyDrive/train_dataset.csv", "r")
-        train_reader = csv.DictReader(train)
-        # if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
-        #     os.makedirs(outpath)
-        for row in train_reader:
-            class_name = f"{row['Class_name']}"
-            file_name = f"{row['file_name']}"
-            url = f"{row['file_id']}"
-            path = os.path.join('./img',class_name,file_name)
-            folder = os.path.join('./img',class_name)
-            if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
-                os.makedirs(folder)
-            urllib.request.urlretrieve(url, path)
-
-        reg = open("/content/drive/MyDrive/reg_dataset.csv", "r")
-        reg_reader = csv.DictReader(reg)
-        # if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
-        #     os.makedirs(outpath)
-        for row in reg_reader:
-            class_name = f"{row['Class_name']}"
-            file_name = f"{row['file_name']}"
-            url = f"{row['file_id']}"
-            path = os.path.join('./reg',class_name,file_name)
-            folder = os.path.join('./reg',class_name)
-            if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
-                os.makedirs(folder)
-            urllib.request.urlretrieve(url, path)
-
-    def _generate_examples(self, filepath, split):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                data = csv.loads(row)
-                if self.config.name == "train":  
-                    yield key, {
-                        "Class_name": datasets.Value("string"),
-                        "file_name": datasets.Value("string"),
-                        "file_id": datasets.Value("string")
-                    }
-                else:  
-                    yield key, {
-                        "Class_name": datasets.Value("string"),
-                        "file_name": datasets.Value("string"),
-                        "file_id": datasets.Value("string")
-                    }
-