Datasets:

HuggingFaceM4
/

something_something_v2

+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+languages:
+- en
+licenses:
+- other-charades
+multilinguality:
+- monolingual
+paperswithcode_id: something-something
+pretty_name: Something Something v2
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- other
+task_ids:
+- other
+---
+# Dataset Card for Something Something v2
+## 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://prior.allenai.org/projects/charades
+- **Repository:** https://github.com/gsig/charades-algorithms
+- **Paper:** https://arxiv.org/abs/1604.01753
+- **Leaderboard:** https://paperswithcode.com/sota/action-classification-on-charades
+- **Point of Contact:** mailto: [email protected]
+### Dataset Summary
+The Something-Something dataset (version 2) is a collection of 220,847 labeled video clips of humans performing pre-defined, basic actions with everyday objects. It is designed to train machine learning models in fine-grained understanding of human hand gestures like putting something into something, turning something upside down and covering something with something.
+### Supported Tasks and Leaderboards
+- `action-classification`: The goal of this task is to classify actions happening in a video. This is a multilabel classification. The leaderboard is available [here](https://paperswithcode.com/sota/action-classification-on-charades)
+### Languages
+The annotations in the dataset are in English.
+## Dataset Structure
+### Data Instances
+```
+{
+  "video_id": "46GP8",
+  "video": "/home/amanpreet_huggingface_co/.cache/huggingface/datasets/downloads/extracted/3f022da5305aaa189f09476dbf7d5e02f6fe12766b927c076707360d00deb44d/46GP8.mp4",
+  "subject": "HR43",
+  "scene": "Kitchen",
+  "quality": 6,
+  "relevance": 7,
+  "verified": "Yes",
+  "script": "A person cooking on a stove while watching something out a window.",
+  "objects": ["food", "stove", "window"],
+  "descriptions": [
+    "A person cooks food on a stove before looking out of a window."
+  ],
+  "labels": [92, 147],
+  "action_timings": [
+    [11.899999618530273, 21.200000762939453],
+    [0.0, 12.600000381469727]
+  ],
+  "length": 24.829999923706055
+}
+```
+### Data Fields
+- `video_id`: `str` Unique identifier for each video.
+- `video`: `str` Path to the video file
+- `subject`: `str` Unique identifier for each subject in the dataset
+- `scene`: `str` One of 15 indoor scenes in the dataset, such as Kitchen
+- `quality`: `int` The quality of the video judged by an annotator (7-point scale, 7=high quality), -100 if missing
+- `relevance`: `int` The relevance of the video to the script judged by an annotated (7-point scale, 7=very relevant), -100 if missing
+- `verified`: `str` 'Yes' if an annotator successfully verified that the video matches the script, else 'No'
+- `script`: `str` The human-generated script used to generate the video
+- `descriptions`: `List[str]` List of descriptions by annotators watching the video
+- `labels`: `List[int]` Multi-label actions found in the video. Indices from 0 to 156.
+- `action_timings`: `List[Tuple[int, int]]` Timing where each of the above actions happened.
+- `length`: `float` The length of the video in seconds
+<details>
+  <summary>
+  Click here to see the full list of ImageNet class labels mapping:
+  </summary>
+</details>
+### Data Splits
+|             |train  |validation| test  |
+|-------------|------:|---------:|------:|
+|# of examples|1281167|50000     |100000 |
+## Dataset Creation
+### Curation Rationale
+### Source Data
+#### Initial Data Collection and Normalization
+#### Who are the source language producers?
+### Annotations
+#### Annotation process
+#### Who are the annotators?
+### Personal and Sensitive Information
+## 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
+### Licensing Information
+### Citation Information
+```bibtex
+@inproceedings{goyal2017something,
+  title={The" something something" video database for learning and evaluating visual common sense},
+  author={Goyal, Raghav and Ebrahimi Kahou, Samira and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others},
+  booktitle={Proceedings of the IEEE international conference on computer vision},
+  pages={5842--5850},
+  year={2017}
+}
+```
+### Contributions
+Thanks to [@apsdehal](https://github.com/apsdehal) for adding this dataset.

classes.py ADDED Viewed

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+# coding=utf-8
+# Copyright 2022 the HuggingFace Datasets Authors.
+#
+# 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.
+from collections import OrderedDict
+SOMETHING_SOMETHING_V2_CLASSES = [
+    "Approaching something with your camera",
+    "Attaching something to something",
+    "Bending something so that it deforms",
+    "Bending something until it breaks",
+    "Burying something in something",
+    "Closing something",
+    "Covering something with something",
+    "Digging something out of something",
+    "Dropping something behind something",
+    "Dropping something in front of something",
+    "Dropping something into something",
+    "Dropping something next to something",
+    "Dropping something onto something",
+    "Failing to put something into something because something does not fit",
+    "Folding something",
+    "Hitting something with something",
+    "Holding something",
+    "Holding something behind something",
+    "Holding something in front of something",
+    "Holding something next to something",
+    "Holding something over something",
+    "Laying something on the table on its side, not upright",
+    "Letting something roll along a flat surface",
+    "Letting something roll down a slanted surface",
+    "Letting something roll up a slanted surface, so it rolls back down",
+    "Lifting a surface with something on it but not enough for it to slide down",
+    "Lifting a surface with something on it until it starts sliding down",
+    "Lifting something up completely without letting it drop down",
+    "Lifting something up completely, then letting it drop down",
+    "Lifting something with something on it",
+    "Lifting up one end of something without letting it drop down",
+    "Lifting up one end of something, then letting it drop down",
+    "Moving away from something with your camera",
+    "Moving part of something",
+    "Moving something across a surface until it falls down",
+    "Moving something across a surface without it falling down",
+    "Moving something and something away from each other",
+    "Moving something and something closer to each other",
+    "Moving something and something so they collide with each other",
+    "Moving something and something so they pass each other",
+    "Moving something away from something",
+    "Moving something away from the camera",
+    "Moving something closer to something",
+    "Moving something down",
+    "Moving something towards the camera",
+    "Moving something up",
+    "Opening something",
+    "Picking something up",
+    "Piling something up",
+    "Plugging something into something",
+    "Plugging something into something but pulling it right out as you remove your hand",
+    "Poking a hole into some substance",
+    "Poking a hole into something soft",
+    "Poking a stack of something so the stack collapses",
+    "Poking a stack of something without the stack collapsing",
+    "Poking something so it slightly moves",
+    "Poking something so lightly that it doesn't or almost doesn't move",
+    "Poking something so that it falls over",
+    "Poking something so that it spins around",
+    "Pouring something into something",
+    "Pouring something into something until it overflows",
+    "Pouring something onto something",
+    "Pouring something out of something",
+    "Pretending or failing to wipe something off of something",
+    "Pretending or trying and failing to twist something",
+    "Pretending to be tearing something that is not tearable",
+    "Pretending to close something without actually closing it",
+    "Pretending to open something without actually opening it",
+    "Pretending to pick something up",
+    "Pretending to poke something",
+    "Pretending to pour something out of something, but something is empty",
+    "Pretending to put something behind something",
+    "Pretending to put something into something",
+    "Pretending to put something next to something",
+    "Pretending to put something on a surface",
+    "Pretending to put something onto something",
+    "Pretending to put something underneath something",
+    "Pretending to scoop something up with something",
+    "Pretending to spread air onto something",
+    "Pretending to sprinkle air onto something",
+    "Pretending to squeeze something",
+    "Pretending to take something from somewhere",
+    "Pretending to take something out of something",
+    "Pretending to throw something",
+    "Pretending to turn something upside down",
+    "Pulling something from behind of something",
+    "Pulling something from left to right",
+    "Pulling something from right to left",
+    "Pulling something onto something",
+    "Pulling something out of something",
+    "Pulling two ends of something but nothing happens",
+    "Pulling two ends of something so that it gets stretched",
+    "Pulling two ends of something so that it separates into two pieces",
+    "Pushing something from left to right",
+    "Pushing something from right to left",
+    "Pushing something off of something",
+    "Pushing something onto something",
+    "Pushing something so it spins",
+    "Pushing something so that it almost falls off but doesn't",
+    "Pushing something so that it falls off the table",
+    "Pushing something so that it slightly moves",
+    "Pushing something with something",
+    "Putting number of something onto something",
+    "Putting something and something on the table",
+    "Putting something behind something",
+    "Putting something in front of something",
+    "Putting something into something",
+    "Putting something next to something",
+    "Putting something on a flat surface without letting it roll",
+    "Putting something on a surface",
+    "Putting something on the edge of something so it is not supported and falls down",
+    "Putting something onto a slanted surface but it doesn't glide down",
+    "Putting something onto something",
+    "Putting something onto something else that cannot support it so it falls down",
+    "Putting something similar to other things that are already on the table",
+    "Putting something that can't roll onto a slanted surface, so it slides down",
+    "Putting something that can't roll onto a slanted surface, so it stays where it is",
+    "Putting something that cannot actually stand upright upright on the table, so it falls on its side",
+    "Putting something underneath something",
+    "Putting something upright on the table",
+    "Putting something, something and something on the table",
+    "Removing something, revealing something behind",
+    "Rolling something on a flat surface",
+    "Scooping something up with something",
+    "Showing a photo of something to the camera",
+    "Showing something behind something",
+    "Showing something next to something",
+    "Showing something on top of something",
+    "Showing something to the camera",
+    "Showing that something is empty",
+    "Showing that something is inside something",
+    "Something being deflected from something",
+    "Something colliding with something and both are being deflected",
+    "Something colliding with something and both come to a halt",
+    "Something falling like a feather or paper",
+    "Something falling like a rock",
+    "Spilling something behind something",
+    "Spilling something next to something",
+    "Spilling something onto something",
+    "Spinning something so it continues spinning",
+    "Spinning something that quickly stops spinning",
+    "Spreading something onto something",
+    "Sprinkling something onto something",
+    "Squeezing something",
+    "Stacking number of something",
+    "Stuffing something into something",
+    "Taking one of many similar things on the table",
+    "Taking something from somewhere",
+    "Taking something out of something",
+    "Tearing something into two pieces",
+    "Tearing something just a little bit",
+    "Throwing something",
+    "Throwing something against something",
+    "Throwing something in the air and catching it",
+    "Throwing something in the air and letting it fall",
+    "Throwing something onto a surface",
+    "Tilting something with something on it slightly so it doesn't fall down",
+    "Tilting something with something on it until it falls off",
+    "Tipping something over",
+    "Tipping something with something in it over, so something in it falls out",
+    "Touching (without moving) part of something",
+    "Trying but failing to attach something to something because it doesn't stick",
+    "Trying to bend something unbendable so nothing happens",
+    "Trying to pour something into something, but missing so it spills next to it",
+    "Turning something upside down",
+    "Turning the camera downwards while filming something",
+    "Turning the camera left while filming something",
+    "Turning the camera right while filming something",
+    "Turning the camera upwards while filming something",
+    "Twisting (wringing) something wet until water comes out",
+    "Twisting something",
+    "Uncovering something",
+    "Unfolding something",
+    "Wiping something off of something",
+]

something_something_v2.py ADDED Viewed

	@@ -0,0 +1,150 @@

+# 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.
+# Lint as: python3
+"""The Something-Something dataset (version 2) is a collection of 220,847 labeled video clips of humans performing pre-defined, basic actions with everyday objects."""
+import csv
+import json
+import os
+import datasets
+from .classes import SOMETHING_SOMETHING_V2_CLASSES
+_CITATION = """
+@inproceedings{goyal2017something,
+  title={The" something something" video database for learning and evaluating visual common sense},
+  author={Goyal, Raghav and Ebrahimi Kahou, Samira and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others},
+  booktitle={Proceedings of the IEEE international conference on computer vision},
+  pages={5842--5850},
+  year={2017}
+}
+"""
+_DESCRIPTION = """\
+The Something-Something dataset (version 2) is a collection of 220,847 labeled video clips of humans performing pre-defined, basic actions with everyday objects. It is designed to train machine learning models in fine-grained understanding of human hand gestures like putting something into something, turning something upside down and covering something with something.
+"""
+class SomethingSomethingV2(datasets.GeneratorBasedBuilder):
+    """Charades is dataset composed of 9848 videos of daily indoors activities collected through Amazon Mechanical Turk"""
+    BUILDER_CONFIGS = [datasets.BuilderConfig(name="default")]
+    DEFAULT_CONFIG_NAME = "default"
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "video_id": datasets.Value("string"),
+                    "video": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "labels": datasets.features.ClassLabel(
+                            num_classes=len(SOMETHING_SOMETHING_V2_CLASSES), names=SOMETHING_SOMETHING_V2_CLASSES
+                    ),
+                    "objects": datasets.Sequence(datasets.Value("string")),
+                }
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+    @property
+    def manual_download_instructions(self):
+        return (
+            "To use Something-Something-v2, please download the 19 data files and the labels file "
+            "from 'https://developer.qualcomm.com/software/ai-datasets/something-something'. "
+            "Unzip the 19 files and concatenate the extracts in order into a tar file named '20bn-something-something-v2.tar.gz. "
+            "Use command like `cat 20bn-something-something-v2-?? >> 20bn-something-something-v2.tar.gz` "
+            "Place the labels zip file and the tar file into a folder '/path/to/data/' and load the dataset using "
+            "`load_dataset('something-something-v2', data_dir='/path/to/data')`"
+        )
+    def _split_generators(self, dl_manager, data_dir):
+        labels_path = os.path.join(data_dir, "labels.zip")
+        videos_path = os.path.join(data_dir, "20bn-something-something-v2.tar.gz")
+        if not os.path.exists(labels_path):
+            raise FileNotFoundError(f"labels.zip doesn't exist in {data_dir}. Please follow manual download instructions.")
+        if not os.path.exists(videos_path):
+            raise FileNotFoundError(f"20bn-something-sokmething-v2.tar.gz doesn't exist in {data_dir}. Please follow manual download instructions.")
+        labels_path = dl_manager.extract(labels_path)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "annotation_file": os.path.join(labels_path, "train.json"),
+                    "videos_files": dl_manager.iter_archive(videos_path),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "annotation_file": os.path.join(labels_path, "validation.json"),
+                    "videos_files": dl_manager.iter_archive(videos_path),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "annotation_file": os.path.join(labels_path, "test.json"),
+                    "videos_files": dl_manager.iter_archive(videos_path),
+                    "labels_file": os.path.join(labels_path, "test_labels.csv"),
+                },
+            ),
+        ]
+    def _generate_examples(self, annotation_file, video_files, labels_file=None):
+        data = {}
+        labels = None
+        if labels_file is not None:
+            with open(labels_file, "r", encoding="utf-8") as fobj:
+                labels = {}
+                for label in fobj.readlines():
+                    label = label.strip().split(";")
+                    labels[label[0]] = label[1]
+        with open(annotation_file, "r", encoding="utf-8") as fobj:
+            annotations = json.load(fobj)
+            for annotation in annotations:
+                if "template" in annotation:
+                    annotation["template"] = annotation["template"].replace("[something]", "something")
+                if labels:
+                    annotation["template"] = labels[annotation["id"]]
+                data[annotation["id"]] = annotation
+        idx = 0
+        for path, file in video_files:
+            video_id = os.path.splitext(os.path.split(path)[1])[0]
+            if video_id not in data:
+                continue
+            info = data[video_id]
+            yield idx, {
+                "video_id": video_id,
+                "video": file,
+                "objects": info["objects"],
+                "label": data["template"],
+                "text": data["text"] if "text" in data else -1
+            }
+            idx += 1