Datasets:

asuglia
/

compguesswhat

@@ -19,7 +19,7 @@ class CompguesswhatConfig(datasets.BuilderConfig):
             **kwargs: keyword arguments forwarded to super.
         """
         super(CompguesswhatConfig, self).__init__(
-            version=datasets.Version("0.1.0", "First CompGuessWhat?! release"), **kwargs
         )
         assert gameplay_scenario in (
             "original",
@@ -73,7 +73,7 @@ class Compguesswhat(datasets.GeneratorBasedBuilder):
         ),
     ]
-    VERSION = datasets.Version("0.1.0")
     def _info(self):
         if self.config.gameplay_scenario == "original":
@@ -88,14 +88,27 @@ class Compguesswhat(datasets.GeneratorBasedBuilder):
                         "timestamp": datasets.Value("string"),
                         "status": datasets.Value("string"),
                         "image": {
                             "id": datasets.Value("int32"),
                             "file_name": datasets.Value("string"),
                             "flickr_url": datasets.Value("string"),
                             "coco_url": datasets.Value("string"),
                             "height": datasets.Value("int32"),
                             "width": datasets.Value("int32"),
-                            "vg_id": datasets.Value("int32"),
-                            "vg_url": datasets.Value("string"),
                         },
                         "qas": datasets.features.Sequence(
                             {
@@ -203,7 +216,12 @@ class Compguesswhat(datasets.GeneratorBasedBuilder):
                 datasets.SplitGenerator(
                     name=split_name,
                     gen_kwargs={
-                        "filepath": os.path.join(dl_dir, full_split_name, self.VERSION.version_str, split_filename)
                     },
                 )
             )
@@ -224,6 +242,11 @@ class Compguesswhat(datasets.GeneratorBasedBuilder):
                 del game["questioner_id"]
             ###
             return game["id"], game
         """Yields examples."""

             **kwargs: keyword arguments forwarded to super.
         """
         super(CompguesswhatConfig, self).__init__(
+            version=datasets.Version("0.2.0", "Second CompGuessWhat?! release"), **kwargs
         )
         assert gameplay_scenario in (
             "original",
         ),
     ]
+    VERSION = datasets.Version("0.2.0")
     def _info(self):
         if self.config.gameplay_scenario == "original":
                         "timestamp": datasets.Value("string"),
                         "status": datasets.Value("string"),
                         "image": {
+                            # this is the image ID in GuessWhat?! which corresponds to the MSCOCO id
                             "id": datasets.Value("int32"),
                             "file_name": datasets.Value("string"),
                             "flickr_url": datasets.Value("string"),
                             "coco_url": datasets.Value("string"),
                             "height": datasets.Value("int32"),
                             "width": datasets.Value("int32"),
+                            # this field represents the corresponding image metadata that can be found in VisualGenome
+                            # in the file image_data.json
+                            # We copy it over so that we avoid any confusion or possible wrong URL
+                            # Please use the original image files to resolve photos
+                            "visual_genome": {
+                                "width": datasets.Value("int32"),
+                                "height": datasets.Value("int32"),
+                                "url": datasets.Value("string"),
+                                "coco_id": datasets.Value("int32"),
+                                # this is the actual VisualGenome image ID
+                                # because we can't rely store it as an integer we same it as string
+                                "flickr_id": datasets.Value("string"),
+                                "image_id": datasets.Value("string"),
+                            },
                         },
                         "qas": datasets.features.Sequence(
                             {
                 datasets.SplitGenerator(
                     name=split_name,
                     gen_kwargs={
+                        "filepath": os.path.join(
+                            dl_dir,
+                            full_split_name,
+                            self.VERSION.version_str,
+                            split_filename,
+                        )
                     },
                 )
             )
                 del game["questioner_id"]
             ###
+            if "visual_genome" in game["image"]:
+                # We need to cast it to string so that we avoid issues with int size
+                game["image"]["visual_genome"]["image_id"] = str(game["image"]["visual_genome"]["image_id"])
+                game["image"]["visual_genome"]["flickr_id"] = str(game["image"]["visual_genome"]["flickr_id"])
             return game["id"], game
         """Yields examples."""

create_dummy_data.py CHANGED Viewed

@@ -12,7 +12,12 @@ parser.add_argument(
     required=True,
     help="Data path containing the CompGuessWhat?! datasets (files with 'jsonl.gz' extension)",
 )
-parser.add_argument("--examples", type=int, default=5, help="Number of games to consider in the dummy dataset")
 original_data_files = {
     "train": "compguesswhat.train.jsonl.gz",
     "valid": "compguesswhat.valid.jsonl.gz",
@@ -74,7 +79,7 @@ def main(args):
     with open(dataset_info_path, encoding="utf-8") as in_file:
         dataset_info = json.load(in_file)
-    dataset_version = dataset_info["default"]["version"]["version_str"]
     print(f"Creating dummy data for CompGuessWhat?! {dataset_version}")

     required=True,
     help="Data path containing the CompGuessWhat?! datasets (files with 'jsonl.gz' extension)",
 )
+parser.add_argument(
+    "--examples",
+    type=int,
+    default=5,
+    help="Number of games to consider in the dummy dataset",
+)
 original_data_files = {
     "train": "compguesswhat.train.jsonl.gz",
     "valid": "compguesswhat.valid.jsonl.gz",
     with open(dataset_info_path, encoding="utf-8") as in_file:
         dataset_info = json.load(in_file)
+    dataset_version = dataset_info["compguesswhat-original"]["version"]["version_str"]
     print(f"Creating dummy data for CompGuessWhat?! {dataset_version}")

dataset_infos.json CHANGED Viewed

@@ -1,396 +1 @@
-{
-  "compguesswhat-original": {
-    "description": "\n        CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,\n        in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference\n        scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io\n    ",
-    "citation": "        @inproceedings{suglia2020compguesswhat,\n          title={CompGuessWhat?!: a Multi-task Evaluation Framework for Grounded Language Learning},\n          author={Suglia, Alessandro, Konstas, Ioannis, Vanzo, Andrea, Bastianelli, Emanuele, Desmond Elliott, Stella Frank and Oliver Lemon},\n          booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},\n          year={2020}\n        }\n    ",
-    "homepage": "https://compguesswhat.github.io/",
-    "license": "",
-    "features": {
-      "id": {
-        "dtype": "int32",
-        "id": null,
-        "_type": "Value"
-      },
-      "target_id": {
-        "dtype": "int32",
-        "id": null,
-        "_type": "Value"
-      },
-      "timestamp": {
-        "dtype": "string",
-        "id": null,
-        "_type": "Value"
-      },
-      "status": {
-        "dtype": "string",
-        "id": null,
-        "_type": "Value"
-      },
-      "image": {
-        "id": {
-          "dtype": "int32",
-          "id": null,
-          "_type": "Value"
-        },
-        "file_name": {
-          "dtype": "string",
-          "id": null,
-          "_type": "Value"
-        },
-        "flickr_url": {
-          "dtype": "string",
-          "id": null,
-          "_type": "Value"
-        },
-        "coco_url": {
-          "dtype": "string",
-          "id": null,
-          "_type": "Value"
-        },
-        "height": {
-          "dtype": "int32",
-          "id": null,
-          "_type": "Value"
-        },
-        "width": {
-          "dtype": "int32",
-          "id": null,
-          "_type": "Value"
-        },
-        "vg_id": {
-          "dtype": "int32",
-          "id": null,
-          "_type": "Value"
-        },
-        "vg_url": {
-          "dtype": "string",
-          "id": null,
-          "_type": "Value"
-        }
-      },
-      "qas": {
-        "feature": {
-          "question": {
-            "dtype": "string",
-            "id": null,
-            "_type": "Value"
-          },
-          "answer": {
-            "dtype": "string",
-            "id": null,
-            "_type": "Value"
-          },
-          "id": {
-            "dtype": "int32",
-            "id": null,
-            "_type": "Value"
-          }
-        },
-        "length": -1,
-        "id": null,
-        "_type": "Sequence"
-      },
-      "objects": {
-        "feature": {
-          "id": {
-            "dtype": "int32",
-            "id": null,
-            "_type": "Value"
-          },
-          "bbox": {
-            "feature": {
-              "dtype": "float32",
-              "id": null,
-              "_type": "Value"
-            },
-            "length": 4,
-            "id": null,
-            "_type": "Sequence"
-          },
-          "category": {
-            "dtype": "string",
-            "id": null,
-            "_type": "Value"
-          },
-          "area": {
-            "dtype": "float32",
-            "id": null,
-            "_type": "Value"
-          },
-          "category_id": {
-            "dtype": "int32",
-            "id": null,
-            "_type": "Value"
-          },
-          "segment": {
-            "feature": {
-              "feature": {
-                "dtype": "float32",
-                "id": null,
-                "_type": "Value"
-              },
-              "length": -1,
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-              "_type": "Sequence"
-            },
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-            "id": null,
-            "_type": "Sequence"
-          }
-        },
-        "length": -1,
-        "id": null,
-        "_type": "Sequence"
-      }
-    },
-    "supervised_keys": null,
-    "builder_name": "compguesswhat",
-    "config_name": "compguesswhat-original",
-    "version": {
-      "version_str": "0.1.0",
-      "description": "First CompGuessWhat?! release",
-      "datasets_version_to_prepare": null,
-      "major": 0,
-      "minor": 1,
-      "patch": 0
-    },
-    "splits": {
-      "train": {
-        "name": "train",
-        "num_bytes": 125184123,
-        "num_examples": 46277,
-        "dataset_name": "compguesswhat"
-      },
-      "validation": {
-        "name": "validation",
-        "num_bytes": 25732027,
-        "num_examples": 9716,
-        "dataset_name": "compguesswhat"
-      },
-      "test": {
-        "name": "test",
-        "num_bytes": 25729944,
-        "num_examples": 9619,
-        "dataset_name": "compguesswhat"
-      }
-    },
-    "download_checksums": {
-      "https://www.dropbox.com/s/l0nc13udml6vs0w/compguesswhat-original.zip?dl=1": {
-        "num_bytes": 106008376,
-        "checksum": "a75567d024fd3992ee5d4d370db7b6d071384c89a0a76ec9c94bc0f4968a54fe"
-      }
-    },
-    "download_size": 106008376,
-    "dataset_size": 176646094,
-    "size_in_bytes": 282654470
-  },
-  "compguesswhat-zero_shot": {
-    "description": "\n        CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,\n        in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference\n        scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io\n    ",
-    "citation": "        @inproceedings{suglia2020compguesswhat,\n          title={CompGuessWhat?!: a Multi-task Evaluation Framework for Grounded Language Learning},\n          author={Suglia, Alessandro, Konstas, Ioannis, Vanzo, Andrea, Bastianelli, Emanuele, Desmond Elliott, Stella Frank and Oliver Lemon},\n          booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},\n          year={2020}\n        }\n    ",
-    "homepage": "https://compguesswhat.github.io/",
-    "license": "",
-    "features": {
-      "id": {
-        "dtype": "int32",
-        "id": null,
-        "_type": "Value"
-      },
-      "target_id": {
-        "dtype": "string",
-        "id": null,
-        "_type": "Value"
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-        "dtype": "string",
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-    "config_name": "compguesswhat-zero_shot",
-    "version": {
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-      "description": "First CompGuessWhat?! release",
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-}


1	+ {"compguesswhat-original": {"description": "\n CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,\n in particular concerning attribute grounding. Use this dataset if you want to use the set of games whose reference\n scene is an image in VisualGenome. Visit the website for more details: https://compguesswhat.github.io\n ", "citation": " @inproceedings{suglia2020compguesswhat,\n title={CompGuessWhat?!: a Multi-task Evaluation Framework for Grounded Language Learning},\n author={Suglia, Alessandro, Konstas, Ioannis, Vanzo, Andrea, Bastianelli, Emanuele, Desmond Elliott, Stella Frank and Oliver Lemon},\n booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},\n year={2020}\n }\n ", "homepage": "https://compguesswhat.github.io/", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "target_id": {"dtype": "int32", "id": null, "_type": "Value"}, "timestamp": {"dtype": "string", "id": null, "_type": "Value"}, "status": {"dtype": "string", "id": null, "_type": "Value"}, "image": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "file_name": {"dtype": "string", "id": null, "_type": "Value"}, "flickr_url": {"dtype": "string", "id": null, "_type": "Value"}, "coco_url": {"dtype": "string", "id": null, "_type": "Value"}, "height": {"dtype": "int32", "id": null, "_type": "Value"}, "width": {"dtype": "int32", "id": null, "_type": "Value"}, "visual_genome": {"width": {"dtype": "int32", "id": null, "_type": "Value"}, "height": {"dtype": "int32", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "coco_id": {"dtype": "int32", "id": null, "_type": "Value"}, "flickr_id": {"dtype": "string", "id": null, "_type": "Value"}, "image_id": {"dtype": "string", "id": null, "_type": "Value"}}}, "qas": {"feature": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "objects": {"feature": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "bbox": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "category": {"dtype": "string", "id": null, "_type": "Value"}, "area": {"dtype": "float32", "id": null, "_type": "Value"}, "category_id": {"dtype": "int32", "id": null, "_type": "Value"}, "segment": {"feature": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "compguesswhat", "config_name": "compguesswhat-original", "version": {"version_str": "0.2.0", "description": "Second CompGuessWhat?! release", "major": 0, "minor": 2, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 123557020, "num_examples": 46341, "dataset_name": "compguesswhat"}, "validation": {"name": "validation", "num_bytes": 25441516, "num_examples": 9738, "dataset_name": "compguesswhat"}, "test": {"name": "test", "num_bytes": 25369315, "num_examples": 9621, "dataset_name": "compguesswhat"}}, "download_checksums": {"https://www.dropbox.com/s/l0nc13udml6vs0w/compguesswhat-original.zip?dl=1": {"num_bytes": 107201655, "checksum": "f965b469142cf65635b2b8b309ba2b28539fd7ad40039b11856cd662f2b000c1"}}, "download_size": 107201655, "post_processing_size": null, "dataset_size": 174367851, "size_in_bytes": 281569506}, "compguesswhat-zero_shot": {"description": "\n CompGuessWhat?! is an instance of a multi-task framework for evaluating the quality of learned neural representations,\n in particular concerning attribute grounding. 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