Add a new configuration in which all the captions associated with an image are listed in a single example (#1)

- Added a new configuration in which all the captions associated with an image are listed in a single example (69b2bc7c69c8c030098cd22f66d6abfee7384d94)

COCO.py

@@ -82,6 +82,21 @@ _FEATURES = datasets.Features(
     }
 )
 
+_FEATURES_CAPTIONS = datasets.Features(
+    {
+        "image": datasets.Image(),
+        "filepath": datasets.Value("string"),
+        "sentids": [datasets.Value("int32")],
+        "filename": datasets.Value("string"),
+        "imgid": datasets.Value("int32"),
+        "split": datasets.Value("string"),
+        "sentences_tokens": [[datasets.Value("string")]],
+        "sentences_raw": [datasets.Value("string")],
+        "sentences_sentid": [datasets.Value("int32")],
+        "cocoid": datasets.Value("int32"),
+    }
+)
+
 
 class COCO(datasets.GeneratorBasedBuilder):
     """COCO"""
@@ -89,7 +104,14 @@ class COCO(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")
 
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="2014", version=VERSION, description="2014 version of COCO with Karpathy annotations and splits"),
+        datasets.BuilderConfig(
+            name="2014", version=VERSION, description="2014 version of COCO with Karpathy annotations and splits"
+        ),
+        datasets.BuilderConfig(
+            name="2014_captions",
+            version=VERSION,
+            description="Same as 2014 but with all captions of one image gathered in a single example",
+        ),
     ]
 
     DEFAULT_CONFIG_NAME = "2014"
@@ -97,7 +119,7 @@ class COCO(datasets.GeneratorBasedBuilder):
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=_FEATURES,
+            features=_FEATURES if self.config.name == "2014" else _FEATURES_CAPTIONS,
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
@@ -135,6 +157,49 @@ class COCO(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, annotation_file, image_folders, split_key):
+        if self.config.name == "2014_captions":
+            return self._generate_examples_2014_captions(annotation_file, image_folders, split_key)
+        elif self.config.name == "2014":
+            return self._generate_examples_2014(annotation_file, image_folders, split_key)
+
+    def _generate_examples_2014_captions(self, annotation_file, image_folders, split_key):
+        with open(annotation_file, "r", encoding="utf-8") as fi:
+            annotations = json.load(fi)
+
+            for image_metadata in annotations["images"]:
+                if split_key == "train":
+                    if image_metadata["split"] != "train" and image_metadata["split"] != "restval":
+                        continue
+                elif split_key == "validation":
+                    if image_metadata["split"] != "val":
+                        continue
+                elif split_key == "test":
+                    if image_metadata["split"] != "test":
+                        continue
+
+                if "val2014" in image_metadata["filename"]:
+                    image_path = image_folders["validation"] / _SPLIT_MAP["validation"]
+                else:
+                    image_path = image_folders["train"] / _SPLIT_MAP["train"]
+
+                image_path = image_path / image_metadata["filename"]
+
+                record = {
+                    "image": str(image_path.absolute()),
+                    "filepath": image_metadata["filename"],
+                    "sentids": image_metadata["sentids"],
+                    "filename": image_metadata["filename"],
+                    "imgid": image_metadata["imgid"],
+                    "split": image_metadata["split"],
+                    "cocoid": image_metadata["cocoid"],
+                    "sentences_tokens": [caption["tokens"] for caption in image_metadata["sentences"]],
+                    "sentences_raw": [caption["raw"] for caption in image_metadata["sentences"]],
+                    "sentences_sentid": [caption["sentid"] for caption in image_metadata["sentences"]],
+                }
+
+                yield record["imgid"], record
+
+    def _generate_examples_2014(self, annotation_file, image_folders, split_key):
         counter = 0
         with open(annotation_file, "r", encoding="utf-8") as fi:
             annotations = json.load(fi)