Update pmc_oa.py

pmc_oa.py

@@ -1,16 +1,12 @@
 """PMC-OA Dataset"""
 
 import os
-raise RuntimeError( os.system('ls') )
-
 import jsonlines
 
 import datasets
 
-
 logger = datasets.logging.get_logger(__name__)
 
-
 _CITATION = """\
 @article{lin2023pmc,
   title={PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents},
@@ -30,56 +26,114 @@ including image-text retrieval on ROCO, MedMNIST image classification, Medical V
 
 _HOMEPAGE = "https://weixionglin.github.io/PMC-CLIP/"
 
-_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"
+_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",
 }
 
 
+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."""
+    """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.",
+        ),
+    ]
 
     def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "caption": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
+        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,
+            )
 
     def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URLS)
- 
-        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']}),
-        ]
+        """Returns SplitGenerators."""
+        downloaded_files = dl_manager.download_and_extract(_URLs)
+        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']}
+                )
+            ]
 
     def _generate_examples(self, filepath, image_dir):
-        """This function returns the examples in the raw (text) form."""
+        """Yields examples."""
         logger.info("generating examples from = %s", filepath)
-
+         
         with jsonlines.open(filepath) as reader:
-            _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
+            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,
+                    }