Update pmc_oa.py

pmc_oa.py

@@ -5,8 +5,10 @@ import jsonlines
 
 import datasets
 
+
 logger = datasets.logging.get_logger(__name__)
 
+
 _CITATION = """\
 @article{lin2023pmc,
   title={PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents},
@@ -26,116 +28,57 @@ including image-text retrieval on ROCO, MedMNIST image classification, Medical V
 
 _HOMEPAGE = "https://weixionglin.github.io/PMC-CLIP/"
 
-_URLs = {
-    "images": "https://huggingface.co/datasets/axiong/pmc_oa/resolve/main/images.zip",
-    "pmc_oa_beta": "https://huggingface.co/datasets/axiong/pmc_oa/resolve/main/pmc_oa_beta.jsonl",
-    "pmc_oa": "https://huggingface.co/datasets/axiong/pmc_oa/resolve/main/pmc_oa.jsonl",
+_URL = "https://huggingface.co/datasets/axiong/pmc_oa/resolve/main/"
+_URLS = {
+    "images": _URL + "images.zip",
+    "train": _URL + "train.jsonl",
+    "valid": _URL + "valid.jsonl",
+    "test": _URL + "test.jsonl"
 }
 
 
-class PMC_OA_Config(datasets.BuilderConfig):
-    """BuilderConfig for PMC_OA"""
-
-    def __init__(self, **kwargs):
-        """
-        Args:
-            **kwargs: keyword arguments forwarded to super.
-        """
-        super(PMC_OA_Config, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-
-
 class PMC_OA(datasets.GeneratorBasedBuilder):
-    """PMC_OA Dataset"""
-
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [
-        PMC_OA_Config(
-            name="pmc_oa_beta",
-            description="<subfigure, caption> pairs. Subfigures detected by a DETR model.",
-        ),
-        PMC_OA_Config(
-            name="pmc_oa",
-            description="<subfigure, subcaption> pairs. Subfigures detected by a DETR model. Subcaptions detected by ChatGPT and aligned with subfigures.",
-        ),
-    ]
+    """PMC_OA Dataset."""
 
     def _info(self):
-        if self.config.name == "pmc_oa_beta":
-            return datasets.DatasetInfo(
-                description=_DESCRIPTION,
-                features=datasets.Features(
-                    {
-                        "image": datasets.Value("string"),
-                        "caption": datasets.Value("string"),
-                    }
-                ),
-                supervised_keys=None,
-                citation=_CITATION,
-                homepage=_HOMEPAGE,
-            )
-        elif self.config.name == "pmc_oa":
-            return datasets.DatasetInfo(
-                description=_DESCRIPTION,
-                features=datasets.Features(
-                    {
-                        "image": datasets.Value("string"),
-                        "caption": datasets.Value("string"),
-                        "alignment_type": datasets.Value("string"),
-                        "alignment_score": datasets.Value("float"),
-                    }
-                ),
-                supervised_keys=None,
-                citation=_CITATION,
-                homepage=_HOMEPAGE,
-            )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "caption": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
 
     def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        downloaded_files = dl_manager.download_and_extract(_URLs)
-        raise RuntimeError(downloaded_files)
-
-        if self.config.name == "pmc_oa_beta":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["pmc_oa_beta"], "image_dir": downloaded_files['images']}
-                )
-            ]
-        elif self.config.name == "pmc_oa":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["pmc_oa"], "image_dir": downloaded_files['images']}
-                )
-            ]
+        data_dir = dl_manager.download_and_extract(_URLS)
+        raise RuntimeError(data_dir)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir['train'], "image_dir": data_dir['images']}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_dir['valid'], "image_dir": data_dir['images']}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir['test'], "image_dir": data_dir['images']}),
+        ]
 
     def _generate_examples(self, filepath, image_dir):
-        """Yields examples."""
+        """This function returns the examples in the raw (text) form."""
         logger.info("generating examples from = %s", filepath)
-         
+
         with jsonlines.open(filepath) as reader:
-            for _id, obj in enumerate(reader):
-                if self.config.name == "pmc_oa_beta":
-                    relative_image_path = obj['image']
-                    image_path = os.path.join(image_dir, "caption_T060_filtered_top4_sep_v0_subfigures", relative_image_path)
-                    caption = obj['caption']
-                    yield _id, {
-                        "image": {
-                            "path": image_path,
-                            "bytes": open(image_path, "rb").read(),
-                        },
-                        "caption": caption,
-                    }
-                elif self.config.name == "pmc_oa":
-                    relative_image_path = obj['image']
-                    image_path = os.path.join(image_dir, "caption_T060_filtered_top4_sep_v0_subfigures", relative_image_path)
-                    caption = obj['caption']
-                    alignment_type = obj['alignment_type']
-                    alignment_score = obj['alignment_score']
-                    yield _id, {
-                        "image": {
-                            "path": image_path,
-                            "bytes": open(image_path, "rb").read(),
-                        },
-                        "caption": caption,
-                        "alignment_type": alignment_type,
-                        "alignment_score": alignment_score,
-                    }
+            _id = 0
+            for obj in reader:
+                relative_image_path = obj['image']
+                image_path = os.path.join(image_dir, "caption_T060_filtered_top4_sep_v0_subfigures", relative_image_path)
+                caption = obj['caption']
+                yield _id, {
+                    "image": {
+                        "path": image_path,
+                        "bytes": open(image_path, "rb").read(),
+                    },
+                    "caption": caption,
+                }
+                _id += 1