Localized Narratives + Readme - open images subset

LocalizedNarratives.py

@@ -0,0 +1,140 @@
+# coding=utf-8
+# Copyright 2022 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.
+"""Localized Narratives"""
+import json
+import datasets
+
+
+_CITATION = """
+@inproceedings{PontTuset_eccv2020,
+  author    = {Jordi Pont-Tuset and Jasper Uijlings and Soravit Changpinyo and Radu Soricut and Vittorio Ferrari},
+  title     = {Connecting Vision and Language with Localized Narratives},
+  booktitle = {ECCV},
+  year      = {2020}
+}
+"""
+
+_DESCRIPTION = """
+Localized Narratives, a new form of multimodal image annotations connecting vision and language.
+We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing.
+Since the voice and the mouse pointer are synchronized, we can localize every single word in the description.
+This dense visual grounding takes the form of a mouse trace segment per word and is unique to our data.
+We annotated 849k images with Localized Narratives: the whole COCO, Flickr30k, and ADE20K datasets, and 671k images of Open Images, all of which we make publicly available.
+"""
+
+_HOMEPAGE = "https://google.github.io/localized-narratives/"
+
+_LICENSE = "CC BY 4.0"
+
+_ANNOTATION_URLs = {
+    "train": [
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00000-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00001-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00002-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00003-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00004-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00005-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00006-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00007-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00008-of-00010.jsonl",
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_train_v6_localized_narratives-00009-of-00010.jsonl",
+    ],
+    "validation": [
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_validation_localized_narratives.jsonl"
+    ],
+    "test": [
+        "https://storage.googleapis.com/localized-narratives/annotations/open_images_test_localized_narratives.jsonl"
+    ],
+}
+
+
+_FEATURES = datasets.Features(
+    {
+        "image": datasets.Image(),
+        "image_url": datasets.Value("string"),
+        "dataset_id": datasets.Value("string"),
+        "image_id": datasets.Value("string"),
+        "annotator_id": datasets.Value("int32"),
+        "caption": datasets.Value("string"),
+        "timed_caption": datasets.Sequence(
+            {
+                "utterance": datasets.Value("string"),
+                "start_time": datasets.Value("float32"),
+                "end_time": datasets.Value("float32"),
+            }
+        ),
+        "traces": datasets.Sequence(
+            datasets.Sequence(
+                {
+                    "x": datasets.Value("float32"),
+                    "y": datasets.Value("float32"),
+                    "t": datasets.Value("float32"),
+                }
+            )
+        ),
+        "voice_recording": datasets.Value("string"),
+    }
+)
+
+
+class LocalizedNarrativesOpenImages(datasets.GeneratorBasedBuilder):
+    """Builder for Localized Narratives."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="OpenImages", version=VERSION, description="OpenImages subset of Localized Narratives"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "OpenImages"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=_FEATURES,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        annotation_files = dl_manager.download(_ANNOTATION_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=split_name,
+                gen_kwargs={"annotation_list": annotation_list, "split": split_name},
+            )
+            for split_name, annotation_list in annotation_files.items()
+        ]
+
+    def _generate_examples(self, annotation_list: str, split: str):
+        counter = 0
+        for annotation_file in annotation_list:
+            with open(annotation_file, "r", encoding="utf-8") as fi:
+                for line in fi:
+                    annotation = json.loads(line)
+                    image_url = f"https://s3.amazonaws.com/open-images-dataset/{split}/{annotation['image_id']}.jpg"
+                    yield counter, {
+                        "image": image_url,
+                        "image_url": image_url,
+                        "dataset_id": annotation["dataset_id"],
+                        "image_id": annotation["image_id"],
+                        "annotator_id": annotation["annotator_id"],
+                        "caption": annotation["caption"],
+                        "timed_caption": annotation["timed_caption"],
+                        "traces": annotation["traces"],
+                        "voice_recording": annotation["voice_recording"],
+                    }
+                    counter += 1

README.md

@@ -1,3 +1,151 @@
 ---
 license: cc-by-4.0
 ---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [https://google.github.io/localized-narratives/(https://google.github.io/localized-narratives/)
+- **Repository:**: [https://github.com/google/localized-narratives](https://github.com/google/localized-narratives)
+- **Paper:** [Connecting Vision and Language with Localized Narratives](https://arxiv.org/pdf/1912.03098.pdf)
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+Localized Narratives, a new form of multimodal image annotations connecting vision and language.
+We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing.
+Since the voice and the mouse pointer are synchronized, we can localize every single word in the description.
+This dense visual grounding takes the form of a mouse trace segment per word and is unique to our data.
+We annotated 849k images with Localized Narratives: the whole COCO, Flickr30k, and ADE20K datasets, and 671k images of Open Images, all of which we make publicly available.
+
+As of now, there is only the OpenImages subset, but feel free to contribute the other subset of Localized Narratives!
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+Each instance has the following structure:
+```
+{
+  dataset_id: 'mscoco_val2017',
+  image_id: '137576',
+  annotator_id: 93,
+  caption: 'In this image there are group of cows standing and eating th...',
+  timed_caption: [{'utterance': 'In this', 'start_time': 0.0, 'end_time': 0.4}, ...],
+  traces: [[{'x': 0.2086, 'y': -0.0533, 't': 0.022}, ...], ...],
+  voice_recording: 'coco_val/coco_val_137576_93.ogg'
+}
+```
+
+### Data Fields
+
+Each line represents one Localized Narrative annotation on one image by one annotator and has the following fields:
+
+- `dataset_id`: String identifying the dataset and split where the image belongs, e.g. mscoco_val2017.
+- `image_id` String identifier of the image, as specified on each dataset.
+- `annotator_id` Integer number uniquely identifying each annotator.
+- `caption` Image caption as a string of characters.
+- `timed_caption` List of timed utterances, i.e. {utterance, start_time, end_time} where utterance is a word (or group of words) and (start_time, end_time) is the time during which it was spoken, with respect to the start of the recording.
+- `traces` List of trace segments, one between each time the mouse pointer enters the image and goes away from it. Each trace segment is represented as a list of timed points, i.e. {x, y, t}, where x and y are the normalized image coordinates (with origin at the top-left corner of the image) and t is the time in seconds since the start of the recording. Please note that the coordinates can go a bit beyond the image, i.e. <0 or >1, as we recorded the mouse traces including a small band around the image.
+- `voice_recording` Relative URL path with respect to https://storage.googleapis.com/localized-narratives/voice-recordings where to find the voice recording (in OGG format) for that particular image.
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@VictorSanh](https://github.com/VictorSanh) for adding this dataset.