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

#1
by SaulLu - opened
Files changed (1) hide show
  1. COCO.py +67 -2
COCO.py CHANGED
@@ -82,6 +82,21 @@ _FEATURES = datasets.Features(
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  }
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  )
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  class COCO(datasets.GeneratorBasedBuilder):
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  """COCO"""
@@ -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(name="2014", version=VERSION, description="2014 version of COCO with Karpathy annotations and splits"),
 
 
 
 
 
 
 
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  ]
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  DEFAULT_CONFIG_NAME = "2014"
@@ -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,
@@ -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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+
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101
  class COCO(datasets.GeneratorBasedBuilder):
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  """COCO"""
 
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  VERSION = datasets.Version("1.0.0")
105
 
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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,
 
157
  ]
158
 
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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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+
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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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+
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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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+
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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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+
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+ image_path = image_path / image_metadata["filename"]
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+
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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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+
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+ yield record["imgid"], record
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+
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+ def _generate_examples_2014(self, annotation_file, image_folders, split_key):
203
  counter = 0
204
  with open(annotation_file, "r", encoding="utf-8") as fi:
205
  annotations = json.load(fi)