Upload VIST.py

VIST.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# TODO: Address all TODOs and remove all explanatory comments
+"""TODO: Add a description here."""
+
+
+import json
+import os
+
+import datasets
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "http://visionandlanguage.net/VIST/dataset.html"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+_URLS = {
+    "DII": {
+        "train": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/train.dii.jsonl.zip",
+        "test": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/test.dii.jsonl.zip",
+        "val": "https://huggingface.co/datasets/NimaBoscarino/VIST/resolve/main/data/val.dii.jsonl.zip",
+    },
+    "SIS": "http://visionandlanguage.net/VIST/json_files/story-in-sequence/SIS-with-labels.tar.gz",
+}
+
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class VIST(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="DII", version=VERSION, description=""),
+        datasets.BuilderConfig(name="SIS", version=VERSION, description=""),
+    ]
+
+    def _info(self):
+        features = None
+        if self.config.name == "DII":
+            features = datasets.Features({
+                'description': datasets.Value("string"),
+                'title': datasets.Value("string"),
+                'farm': datasets.ClassLabel(num_classes=10),  # Actually 9, but datasets complains for some reason?
+                'date_update': datasets.Value("timestamp[s]"),
+                'primary': datasets.Value("int32"),
+                'server': datasets.Value("int16"),
+                'date_create': datasets.Value("timestamp[s]"),
+                'photos': datasets.Value("int16"),
+                'secret': datasets.Value("string"),
+                'owner': datasets.Value("string"),
+                'vist_label': datasets.Value("string"),
+                'id': datasets.Value("int64"),
+                "images": datasets.Sequence({
+                    'datetaken': datasets.Value("date64"),
+                    'license': datasets.ClassLabel(num_classes=7),
+                    'image_title': datasets.Value("string"),
+                    'longitude': datasets.Value("float64"),
+                    'url': datasets.Image(decode=False),
+                    'image_secret': datasets.Value("string"),
+                    'media': datasets.ClassLabel(num_classes=2, names=["photo", "video"]),
+                    'latitude': datasets.Value("float64"),
+                    'image_id': datasets.Value("int64"),
+                    'tags': [datasets.Value("string")],
+                    'image_farm': datasets.ClassLabel(names=["1", "2", "6", "7"]),  # From exploring the data
+                    'image_server': datasets.Value("int16"),
+                    "annotations": datasets.Sequence({
+                        'original_text': datasets.Value("string"),
+                        'photo_order_in_story': datasets.Value("int8"),
+                        'worker_id': datasets.ClassLabel(names_file="/Users/nima/Work/sandbox/datasets/VIST/dii.worker_ids.csv"),
+                        'text': datasets.Value("string"),
+                    })
+                })
+            })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[self.config.name]
+        data_dirs = dl_manager.download_and_extract(urls)
+
+        for split in data_dirs:
+            archive_path = data_dirs[split]
+            if archive_path.endswith(".zip") or os.path.isdir(archive_path):
+                data_dirs[split] = os.path.join(archive_path, os.listdir(archive_path)[0])
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dirs["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": data_dirs["val"],
+                    "split": "validation",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": data_dirs["test"],
+                    "split": "test"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as f:
+            for key, row in enumerate(f):
+                data = json.loads(row)
+                yield key, data