Upload fusing_fill50k.py

fusing_fill50k.py

@@ -5,18 +5,21 @@ import os
 
 _VERSION = datasets.Version("0.0.2")
 
-_DESCRIPTION = "TODO"
-_HOMEPAGE = "TODO"
-_LICENSE = "TODO"
-_CITATION = "TODO"
-
-_FEATURES = datasets.Features(
-    {
-        "image": datasets.Image(),
-        "conditioning_image": datasets.Image(),
-        "text": datasets.Value("string"),
-    },
-)
+_DESCRIPTION = "This dataset includes images and conditioning images for XYZ purpose."
+_HOMEPAGE = "https://www.example.com"
+_LICENSE = "MIT"
+_CITATION = """@article{YourDataset2021,
+  title={Your Dataset Title},
+  author={Your Name},
+  journal={Your Journal},
+  year={2021}
+}"""
+
+_FEATURES = datasets.Features({
+    "image": datasets.Value("string"),  # Change from datasets.Image() to Value("string") if using paths directly
+    "conditioning_image": datasets.Value("string"),
+    "text": datasets.Value("string"),
+})
 
 METADATA_URL = hf_hub_url(
     "spine-crook/test_dataset",
@@ -38,7 +41,6 @@ CONDITIONING_IMAGES_URL = hf_hub_url(
 
 _DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
 
-
 class Fill50k(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [_DEFAULT_CONFIG]
     DEFAULT_CONFIG_NAME = "default"
@@ -56,14 +58,11 @@ class Fill50k(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         metadata_path = dl_manager.download(METADATA_URL)
         images_dir = dl_manager.download_and_extract(IMAGES_URL)
-        conditioning_images_dir = dl_manager.download_and_extract(
-            CONDITIONING_IMAGES_URL
-        )
+        conditioning_images_dir = dl_manager.download_and_extract(CONDITIONING_IMAGES_URL)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "metadata_path": metadata_path,
                     "images_dir": images_dir,
@@ -77,25 +76,11 @@ class Fill50k(datasets.GeneratorBasedBuilder):
 
         for _, row in metadata.iterrows():
             text = row["text"]
-
-            image_path = row["image"]
-            image_path = os.path.join(images_dir, image_path)
-            image = open(image_path, "rb").read()
-
-            conditioning_image_path = row["conditioning_image"]
-            conditioning_image_path = os.path.join(
-                conditioning_images_dir, row["conditioning_image"]
-            )
-            conditioning_image = open(conditioning_image_path, "rb").read()
+            image_path = os.path.join(images_dir, row["image"])
+            conditioning_image_path = os.path.join(conditioning_images_dir, row["conditioning_image"])
 
             yield row["image"], {
                 "text": text,
-                "image": {
-                    "path": image_path,
-                    "bytes": image,
-                },
-                "conditioning_image": {
-                    "path": conditioning_image_path,
-                    "bytes": conditioning_image,
-                },
-            }
+                "image": image_path,
+                "conditioning_image": conditioning_image_path,
+            }