Add a new configuration in which all the captions associated with an image are listed in a single example
#1
by
SaulLu
- opened
COCO.py
CHANGED
@@ -82,6 +82,21 @@ _FEATURES = datasets.Features(
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}
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class COCO(datasets.GeneratorBasedBuilder):
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"""COCO"""
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@@ -89,7 +104,14 @@ class COCO(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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]
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DEFAULT_CONFIG_NAME = "2014"
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@@ -97,7 +119,7 @@ class COCO(datasets.GeneratorBasedBuilder):
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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-
features=_FEATURES,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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@@ -135,6 +157,49 @@ class COCO(datasets.GeneratorBasedBuilder):
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]
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def _generate_examples(self, annotation_file, image_folders, split_key):
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counter = 0
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with open(annotation_file, "r", encoding="utf-8") as fi:
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annotations = json.load(fi)
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}
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)
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_FEATURES_CAPTIONS = datasets.Features(
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{
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"image": datasets.Image(),
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"filepath": datasets.Value("string"),
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"sentids": [datasets.Value("int32")],
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"filename": datasets.Value("string"),
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"imgid": datasets.Value("int32"),
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"split": datasets.Value("string"),
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"sentences_tokens": [[datasets.Value("string")]],
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"sentences_raw": [datasets.Value("string")],
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"sentences_sentid": [datasets.Value("int32")],
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"cocoid": datasets.Value("int32"),
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}
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)
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class COCO(datasets.GeneratorBasedBuilder):
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"""COCO"""
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="2014", version=VERSION, description="2014 version of COCO with Karpathy annotations and splits"
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),
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datasets.BuilderConfig(
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name="2014_captions",
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version=VERSION,
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description="Same as 2014 but with all captions of one image gathered in a single example",
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),
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]
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DEFAULT_CONFIG_NAME = "2014"
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=_FEATURES if self.config.name == "2014" else _FEATURES_CAPTIONS,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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]
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def _generate_examples(self, annotation_file, image_folders, split_key):
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if self.config.name == "2014_captions":
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return self._generate_examples_2014_captions(annotation_file, image_folders, split_key)
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elif self.config.name == "2014":
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return self._generate_examples_2014(annotation_file, image_folders, split_key)
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def _generate_examples_2014_captions(self, annotation_file, image_folders, split_key):
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with open(annotation_file, "r", encoding="utf-8") as fi:
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annotations = json.load(fi)
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for image_metadata in annotations["images"]:
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if split_key == "train":
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if image_metadata["split"] != "train" and image_metadata["split"] != "restval":
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continue
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elif split_key == "validation":
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if image_metadata["split"] != "val":
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continue
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elif split_key == "test":
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if image_metadata["split"] != "test":
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continue
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if "val2014" in image_metadata["filename"]:
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image_path = image_folders["validation"] / _SPLIT_MAP["validation"]
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else:
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image_path = image_folders["train"] / _SPLIT_MAP["train"]
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image_path = image_path / image_metadata["filename"]
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record = {
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"image": str(image_path.absolute()),
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"filepath": image_metadata["filename"],
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"sentids": image_metadata["sentids"],
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"filename": image_metadata["filename"],
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"imgid": image_metadata["imgid"],
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"split": image_metadata["split"],
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"cocoid": image_metadata["cocoid"],
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"sentences_tokens": [caption["tokens"] for caption in image_metadata["sentences"]],
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"sentences_raw": [caption["raw"] for caption in image_metadata["sentences"]],
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"sentences_sentid": [caption["sentid"] for caption in image_metadata["sentences"]],
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}
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yield record["imgid"], record
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def _generate_examples_2014(self, annotation_file, image_folders, split_key):
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counter = 0
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with open(annotation_file, "r", encoding="utf-8") as fi:
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annotations = json.load(fi)
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