dataset script

stained-glass.py

@@ -0,0 +1,52 @@
+"""Dataset class for stained-glass dataset."""
+
+import datasets
+import os
+import pandas as pd
+
+_DESCRIPTION = """Dataset consists of 21 high-resolution images of stained glass art, accompanied by corresponding captions"""
+_HOMEPAGE = """https://huggingface.co/datasets/abinthomasonline/stained-glass"""
+_ADJECTIVES = ["", "good", "cropped", "clean", "bright", "cool", "nice", "small", "large", "dark", "weird"]
+
+
+class StainedGlass(datasets.GeneratorBasedBuilder):
+    """Stained Glass Images dataset"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION, 
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "caption": datasets.Value(),
+                }
+            ),
+            supervised_keys=("image", "caption"),
+            homepage=_HOMEPAGE,
+        )
+
+    def _split_generators(self, dl_manager):
+        captions_path = dl_manager.download("captions.csv")
+        df = pd.read_csv(captions_path, header=None)
+        image_paths = [os.path.join("images", row[0]) for _, row in df.iterrows()]
+        image_paths = dl_manager.download(image_paths)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "captions_path": captions_path,
+                    "image_paths": image_paths,
+                },
+            )
+        ]
+
+    def _generate_examples(self, captions_path, image_paths):
+        df = pd.read_csv(captions_path, header=None)
+        captions = {row[0]: row[1].replace('"', '') for _, row in df.iterrows()}
+        for adjective in _ADJECTIVES:
+            for i, image_path in enumerate(image_paths):
+                yield i, {
+                    "image": image_path,
+                    "caption": captions[os.path.basename(image_path)].format(token='<token>', adjective=adjective),
+                }