Upload image_demo.py

image_demo.py

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+import datasets
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {Small image-text set},
+author={Plaban Nayak},
+year={2023}
+}
+"""
+_DESCRIPTION = """\
+Demo dataset for testing or showing image-text capabilities.
+"""
+_HOMEPAGE = "https://huggingface.co/datasets/Plaban81/image-text-demo"
+
+_LICENSE = ""
+
+_REPO = "https://huggingface.co/datasets/Plaban81/image-text-demo"
+
+_URL ="https://huggingface.co/datasets/Plaban81/image-demo/resolve/main/image_dataset.tar.gz"
+
+descriptions = ['kajol', 'kagna', 'nohra', 'aish', 'kareena', 'shakti']
+class ImageSet(datasets.GeneratorBasedBuilder):
+    """Small sample of image-text pairs"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    'Name': datasets.Value("string"),
+                    'Image': datasets.Image(),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        images_archive = dl_manager.download(_URL)
+        image_iters = dl_manager.iter_archive(images_archive)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "images": image_iters
+                }
+            ),
+        ]
+
+    def _generate_examples(self, images):
+        """ This function returns the examples in the raw (text) form."""
+        
+        for idx, (filepath, image) in enumerate(images):
+            #description = filepath.split('/')[-1][:-4]
+            #description = description.replace('_', ' ')
+            yield idx, {
+                "image": {"path": filepath, "bytes": image.read()},
+                "text": descriptions[idx],
+            }