Kinetics 400 dataset

Kinetics 400 dataset. Each of these clips are around 10 seconds and they have been taken from YouTube videos. We describe an extension of the DeepMind Kinetics human action dataset from 400 classes, each with at least 400 video clips, to 600 classes, each with at least 600 video clips. The 480K videos are divided into 390K, 30K, 60K for training, validation and test sets, respectively. pip install pyyaml. code. 2) Kinetics-Skeleton Subset (KSS): Kinetics-skeleton is a benchmark dataset used in HAR research that contains OpenPose-COCO extracted skeleton data of Kinetics-400 dataset. Those video clips are from YouTube with a great variety. The dataset contains 400 human action classes, with at least 400 video clips for each action. This subset of Kinetics dataset consists of the 200 categories with most training examples; for each category, we randomly sample 400 examples from the training set, and 25 examples from the validation set, resulting in 80K training examples and 5K validation examples in total. This massive dataset contains 400 I3D models pre-trained on Kinetics also placed first in the CVPR 2017 Charades challenge. 5 K videos. 8% and 93. ) Note that for TAPOS, you need to cut out each action instance by yourself first and then can use our following codes to process each instance's video separately. Raw. Jul 19, 2023 · The Kinetics-400 dataset is an extensive collection of YouTube videos. Open Copy link sailordiary commented Nov 3, 2019. Nov 25, 2019 · The dataset our human activity recognition model was trained on is the Kinetics 400 Dataset. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5`` and Feb 3, 2024 · Specifically for the kinetics-400 dataset, in the paper "Unmasked Teacher: Towards Training-Efficient Video Foundation Models," they provide the following summary for the number of training and validation data: In the Video Swin Transformer paper, they also describe the kinetics-400 dataset as follows: Generic Kinetics dataset. Set the model to eval mode and move to desired device. The Kinetics-400 contains around 240k training videos and 20k validation videos of 10s from 400 classes. device = "cpu" model = model. In [139] , the authors use OpenPose [21] to extract the pose on each frame and then test their skeleton-based action recognition. New Dataset. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5`` and Kinetics数据集的下载 (Kinetics-400和Kinetics-600) 【数据集】Kinetics-600 dataset介绍. Kinetics-100 is a dataset split created from the Kinetics dataset to evaluate the performance of few-shot action recognition models. to(device) Download the id to label mapping for the Kinetics 400 dataset on which the torch hub models were trained. New Model. Awesome video understanding toolkits based on PaddlePaddle. Dec 1, 2023 · Kinetics Skeleton 400 is a large-scale dataset with estimated keypoint locations by Openpose (Cao et al. In this Colab we will use it recognize activities in videos from a UCF101 dataset. If this is the case, then you only need to replace all whitespaces in the class name for ease of processing either by detox 输入如下命令，即可提取K400视频文件的frames. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands Nov 7, 2020 · We carefully perform the ablation study on one of the most challenging and largest-scale action classification dataset – Kinetics-400 as well as on UCF-101 and HMDB-51 datasets. 1. Additionally, each version adds new videos to with only 1% labeled videos in the Kinetics-400 dataset. Saved searches Use saved searches to filter your results more quickly A New Model and the Kinetics Dataset by Joao Carreira and Andrew Zisserman to PyTorch. 该数据集包含 400 个人类动作类，每个动作至少有 400 个视频剪辑。. Run on full Kinetics-400 dataset to verify accuracy claims moabitcoin/ig65m-pytorch#2. See full list on github. Apr 1, 2024 · The Kinetics Skeleton 400 dataset is a comprehensive compilation of approximately 300,000 video clips that were carefully curated from various sources on YouTube. Aug 3, 2018 · A Short Note about Kinetics-600. pip install -U openxlab. json格式. We describe the DeepMind Kinetics human action video dataset. I3D (Inflated 3D Networks) is a widely May 22, 2017 · Kinetics has two orders of magnitude more data, with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. 3. The actions are human focussed and cover a broad range of classes including ::: # MIM 支持下载 Kinetics-400/600/700 数据集。用户可以通过一行命令，从 OpenDataLab 进行下载，并进行预处理。 ```Bash # 安装 OpenXLab CLI 工具 pip install -U openxlab # 登录 OpenXLab openxlab login # 通过 MIM 进行 Kinetics-400 数据集下载，预处理。 The --sets switch dictates how many classes will be included in the metadata. The scripts can be used for preparing kinetics-710. The number of clips for each class in the various splits (left), and the totals (right). The frame resolution of Kinetics-400 we used is with a short-side 320. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5 Finally, we successfully train a video ViT model with a billion parameters, which achieves a new state-of-the-art performance on the datasets of Kinetics (90. The dataset was created from non-professional videos (including clutter, shake/motion situations) taken from YouTube. To give an example, for 2 videos with 10 and 15 frames respectively, if This paper re-evaluates state-of-the-art architectures in light of the new Kinetics Human Action Video dataset. 4. Kinetics-700 is a video dataset of 650,000 clips that covers 700 human action classes. Fig. It is an extensions of the Kinetics-400 dataset. Sep 16, 2021 · Spatiotemporal ResNet-18 for Action Recognition Trained on Kinetics-400 Data Identify the main action in a video Released in 2018, this family of models is obtained by splitting the 3D convolutional filters into distinct spatial and temporal components yielding a significant increase in accuracy. Enter. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5 Continual Spatio-Temporal Graph Convolutional Networks. However, they Jul 1, 2021 · Kinetics. The current state-of-the-art on Kinetics-400 is InternVideo2-6B. Setup. Warn·ing! This work comes with no warranty! Note that some people may already have a backup of the kinetics-400 dataset using the official crawler. Mar 8, 2022 · The Kinetics 400 dataset is from the Kinetics 400 video dataset 25 and OpenPose 26 pose estimation toolbox. 9% on K600) and Something-Something (68. # install OpenDataLab CLI tools. # log in OpenDataLab. tenancy. conda install matplotlib. 5GB) can be downloaded from GoogleDrive or BaiduYun. Kinetics-400 dataset. Kinetics-Skeleton contains 240000 clips of training data and Apr 18, 2023 · VideoMAE works well for video datasets of different scales and can achieve 87. It contains around 300,000 trimmed human action videos from 400 action classes. However, their instruction of dataset preparation is too brief. Each clip lasts around 10s and is taken from a different YouTube video. 2022. 7% on V1 and 77. Other categories focus on the motion properties as different objects perform the same action. 5 K videos and a test set containing about 1. , 2017), containing lots of fine-grained actions that own similar contexts. source activate YOUR_ENV_NAME. The Kinetics skeleton dataset (Yan et al. As as result, everyone might not be using the same Kinetics dataset. 每个剪辑持续大约 10 秒，并且取自不同的 YouTube 视频。. The heart of the transfer is the i3d_tf_to_pt. Kinetics dataset include To obtain the joint locations, we first resized all videos to the resolution of 340x256 and converted the frame rate to 30 fps. Download stops at training set tar file 121 (full k400 dataset is 200+ tar files). Table1compares the size of Kinetics to a number of re-cent human action datasets. md. Kinetics-400 dataset : The Kinetics-400 dataset is a large and well-labelled dataset, which has 400 action classes. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. There are 3 main versions of the dataset; Kinetics 400, Kinetics 600 and the Kinetics 700 version. Kinetics Dataset Labels (name to ID). This year (2017), it served in the ActivityNet challenge as the trimmed video classification track. /rawframes 路径下，大小约为2T左右。. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5 Generic Kinetics dataset. To facilitate the studies, we adopt I3D-50 as our feature backbone unless specified. The version number indicates the number of action classes. The Something-Something V2 is another large-scale video dataset, having around 169k videos for training and 20k videos for validation. Therefore, we will call python create_meta. Kinetics Human-Action dataset. To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5 with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. In this tutorial we will show how to load a pre trained video classification model in PyTorchVideo and run it on a test video. Environments. We employed a testing scheme of 1 clip and center crop for the Something-Something V2 dataset, and utilized 10 clips and 3 crops for testing the Kinetics 400 dataset. Setup Kinetics-700. This dataset consists of: 400 human activity recognition classes; At least 400 video clips per class (downloaded via YouTube) A total of 300,000 videos; You can view the full list of classes the model can recognize here. conda install pillow. 这些动作以人类为中心 Kinetics-400 is an action recognition video dataset. 把videos对应标签的. PyTorchVideo provides several pretrained models through Torch Hub. Tiny-Kinetics-400同样包含400个类别，每个类别下仅有两条视频数据，分为train与val，可用于调试 Kinetics-400/600/700 are action recognition video datasets. The 100 classes are further split into 64, 12, and 24 non-overlapping classes to use as the meta-training set, meta-validation set, and meta-testing set, respectively Kinetics-400 and Kinetics-600 are common video recognition datasets used by popular video understanding projects like SlowFast or PytorchVideo. When pre-trained on a Kinetics Human-Action dataset. The PyTorchVideo Torch Hub models were trained on the Kinetics 400 [1] dataset. This will be used to get the category label names from the predicted class ids. emoji_events. (b) The difference in performance between VIT-B and VIT-S, categorized by class, is evaluated under a supervised training scenario with only 1% labeled videos in the Kinetics-400 dataset. csv和. A New Model and the Kinetics Dataset. # Set to GPU or CPU. name dataset # of frames May 19, 2017 · The dataset is described, the statistics are described, how it was collected, and some baseline performance figures for neural network architectures trained and tested for human action classification on this dataset are given. 7. They can be used for training and exploring neu-ral network architectures for modelling human actions in video. conda install pytorch==1. MMAction2 supports Kinetics-710 dataset as a concat dataset, which means only provides a list of annotation files, and makes use of the original data of Kinetics-400/600/700 dataset. py frames --sets 50 400 --save resources/kinetics_video_frames to generate metadata for 50 randomly chosen classes and for all 400 classes. New Notebook. I know this isn't The Kinetics Human Action Video Dataset. May 5, 2022 · Some notes before preparing the two datasets: We decode the video online to reduce the cost of storage. 0 torchvision==0. py script. Example use case: we want to select the hyper-parameters of our neural networks on a small subset of Kinetics (let's say 50 from the 400 classes) and then train the neural network on the whole dataset. 2 dataset. Dataset card Files Community. These are generated from the training CSV files from each dataset by collecting the unique classes, sorting them, and then numbering them from 0 upwards. 视频文件frames提取完成后，会存储在指定的 . 整个数据集包含400个类别，全部文件大概需要135G左右的存储空间，下载起来比较困难。. UCF-101 [24] and HMDB-51 [26] data are among the most detailed datasets used for human action recognition. In Kinetics-400, some categories are highly correlated with interacting objects or scene context. The Kinetics-400 dataset contains 240 K training data, 40 K test data and 20 K validation data. The results corresponding to each dataset are summarized in Tables 5 and 6 respectively. (Note that some of the videos can not be downloaded from YouTube for some reason, you can go ahead with those available. The Kinetics-600 is a large-scale action recognition dataset which consists of around 480K videos from 600 action categories. Each clip is annotated with an action class and Sep 5, 2023 · On pre-trained of the entire Kinetics-400 dataset and inference on UCF-101, the SVT achieves 90. Exploiting temporal context for 3D human pose estimation in the wild uses temporal information from videos to correct errors in single-image 3D pose estimation. 行为识别数据集 Kinetics. Aug 24, 2021 · An extension of the Kinetics human action dataset from 400 classes to 600 classes was further released as Kinetics-600 . May 19, 2017 · We describe the DeepMind Kinetics human action video dataset. See a full comparison of 200 papers with code. 0) creates a severe bottleneck for the training speed. This dataset consider every video as a collection of video clips of fixed size, specified by ``frames_per_clip``, where the step in frames between each clip is given by ``step_between_clips``. , 2017), by using the OpenPose toolbox (Cao et al. The main purpose for the Kinetics dataset was to become the ImageNet equivalent of video data. 0% on K400 and 89. It supports video data annotation tools, lightweight RGB and skeleton based action recognition model, practical Kinetics-400/600/700 are action recognition video datasets. In this repository, we provide results from applying this algorithm on the Kinetics-400 dataset. As a reference, the statistics of the Kinetics dataset used in PySlowFast ca For basic dataset information, please refer to the paper. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing Apr 25, 2024 · zumba. The increase then was from 10 to 51 classes, and we in turn increase this to 400 classes. Convert sound tracks into a tfrecords file: Loading mp3 files in Tensorflow (as of version 1. Kinetics has two orders of magnitude more data, with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. A year later in 2019, a dataset with 700 action classes was released as Kinetics-700 . Our STGAT achieves new state-of-the-art accuracy on this large-scale in-the-wild dataset. 1: Comparison of performance between different architectural models. Kinetics dataset骨架点分布. 3% on UCF101, and 62. If the issue persists, it's likely a problem on our side. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing Apr 1, 2021 · Kinetics-400 [25] is a large scale dataset widely adopted for evaluating video-based action recognition algorithms. Therefore, this project provides a more detailed instruction for Kinetics-400/-600 data preprocessing. The PyTorchVideo Torch Hub models were trained on the Kinetics 400 dataset and finetuned specifically for detection on AVA v2. The extracted skeleton data we called Kinetics-skeleton (7. Kinetics-400 datasets contains 400 action classes with at least 400 video for each class with a total of 260,000 video clips. We provide an analysis on how current architectures fare on the ::: # MIM 支持下载 Kinetics-400/600/700 数据集。用户可以通过一行命令，从 OpenDataLab 进行下载，并进行预处理。 ```Bash # 安装 OpenXLab CLI 工具 pip install -U openxlab # 登录 OpenXLab openxlab login # 通过 MIM 进行 Kinetics-400 数据集下载，预处理。 cc-by-4. The raw Kinetics doesn't contain skeleton data, and [2] uses OpenPose toolbox to generate skeleton with 18 joints on every frame. This dataset consider every video as a collection of video clips of fixed size, specified by frames_per_clip, where the step in frames between each clip is given by step_between_clips. Labels for these actions can be found in the label map file. MIM supports downloading from OpenDataLab and preprocessing Kinetics-400/600/700 dataset with one command line. The current state-of-the-art on Kinetics-Skeleton dataset is Structured Keypoint Pooling (PPNv2 skeletons+objects). Run the following commands to install the exvironments. See a full comparison of 41 papers with code. KINETICS_LABELS. Jun 13, 2023 · Kinetics-Sound This is a subset of Kinetics-400, introduced in Look, Listen and Learn by Relja Arandjelovic and Andrew Zisserman. With Kinetics-400是视频领域benchmark常用数据集，详细介绍可以参考其官方网站 Kinetics 。. pip install av. These are mapping files that go between class IDs to class names. In terms of variation, although the UCF-101 dataset contains 101 actions with 100+ clips Dec 31, 2020 · There are many links in Kinetics that have expired. table_chart. The number of train / validation data for our experiments is 240436 /19796. GitHub Gist: instantly share code, notes, and snippets. py --rgb to generate the rgb checkpoint weight pretrained from ImageNet inflated initialization. 6. 100 classes are randomly selected from a total of 400 categories, each composed of 100 examples. avi文件转为kinetics400的格式，其中所包含的格式有. , 2019). Then, we extracted skeletons from each frame in Kinetics by Openpose. Kinetics 700 is the latest version at the time of the writing of this blog. Kinetics400 is an action recognition dataset of realistic action videos, collected from YouTube. Getting Started with Pre-trained I3D Models on Kinetcis400¶. 4% on Kinects-400, 75. 7% for linear evaluation and fine-tuning settings, respectively. We’re on a journey to advance and democratize artificial intelligence through open source and open science. As of the writing of this post, four versions of the Kinetics dataset have been released: 400, 600, 700, and 700–2020. The Kinetics datasets are a series of large scale curated datasets of video clips, covering a diverse range of human actions. 0% on V2). This dataset at the time of release, was mainly helpful as there were not many datasets that had a large collection of human action for deep learning. Additionally, each version adds new videos to Jul 9, 2022 · In 2017, DeepMind released one of the largest and most impactful human action recognition datasets yet, Kinetics. Homepage Jun 24, 2022 · The HMDB51 dataset is split into a training set containing about 3. 2. All experiments on Kinetics in MMAction2 are based on this version, we recommend users to try this version. pip install -U opendatalab. Kinetics-400/600/700 are action recognition video datasets. com Feb 13, 2020 · If you are interested in performing deep learning for human activity or action recognition, you are bound to come across the Kinetics dataset released by deep mind. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. Each action class has at least 700 video clips. Jul 9, 2022 · In 2017, DeepMind released one of the largest and most impactful human action recognition datasets yet, Kinetics. The original module was trained on the kinetics-400 dateset and knows about 400 different actions. Three editions have been released: Kinetics-400 [6], Kinetics-600 [1] and Kinetics-700 [2], with 400, 600 and Kinetics-400 [6] 250–1000 50 100 0 246,245 306,245 400 Kinetics-600 450–1000 50 100 around 50 392,622 495,547 600 Table 1: Kinetics Dataset Statistics. To our best knowledge, VideoMAE is the first to achieve the state-of-the-art performance on these four popular benchmarks with the vanilla ViT backbones while doesn't need any Aug 15, 2017 · Kinetics Human Action Video Dataset is a large-scale video action recognition dataset released by Google DeepMind. , 2018) is obtained by extracting skeleton annotations from videos composing the Kinetics 400 dataset (Kay et al. Each video in the dataset is a 10-second clip of action moment annotated from raw YouTube video. In our experiments, the cpu bottleneck issue only appears when input frames are more than 8. 6% on HMDB51. It consists of 240,436 training and 19,796 testing samples, representing a total of 400 action classes. In contrast to Kinetics-400, this dataset contains 174 motion-centric action classes. # log in OpenXLab. Each skeleton is We provide TimeSformer models pretrained on Kinetics-400 (K400), Kinetics-600 (K600), Something-Something-V2 (SSv2), and HowTo100M datasets. New Competition Kinetics-400/600/700 is a large-scale high-quality dataset of YouTube video URLs which includes a diverse range of human focused actions. . Launch it with python i3d_tf_to_pt. 8. Each skeleton graph contains 18 major joints and each joint is represented with a tuple Introduction. [ ] Kinetics Datasets Downloader. Imbalanced-MiniKinetics200 is a subset of Mini-Kinetics-200 with 400 human action classes and over 400 clips per class, and is collected from realistic, challenging YouTube videos. Imbalanced-MiniKinetics200 was proposed by "Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition" to evaluate varying scenarios of video long-tailed recognition. In order to scale up the dataset we changed the data collection process so it uses multiple queries per class, with some of them in a Download datasets from Kinetics-400 and TAPOS. 4% on Something-Something V2, 91. # install OpenXlab CLI tools. Kinetics-400 is an action recognition video dataset. HMDB dataset was that the then current generation of ac-tion datasets was too small. We provide an analysis on how current architectures fare on the task of action classification on this dataset and how much performance improves on the smaller benchmark datasets after pre-training on Kinetics. It contains trimmed videos for 400 daily activities. Available models are described in model zoo documentation. Jul 1, 2022 · The UCF101 dataset contains videos for 101 action classes and at least 100 video clips for each class with a total of 13,320 videos and each video clip is 320*240 pixels. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing Mar 6, 2024 · To ensure a fair comparison, we compare our approach with ResNet-50-based frameworks. For basic dataset information, please refer to the paper. eval() model = model. The original (and official!) tensorflow code can be found here. Due to the high computational cost associated with OpenPose extraction, this already extracted skeleton dataset was used in preliminary model building with Kinectics-400 Aug 26, 2021 · 1、Kinetics-400数据集简介Kinetics-400是一个大规模，高质量的YouTube视频网址数据集，其中包含各种以人为本的行动。. 0 -c pytorch. 3. With 306,245 short trimmed videos from 400 action categories, it is one of the largest and most widely used dataset in the research community for benchmarking state-of-the-art video action recognition models. Oct 19, 2020 · The Kinetics-400 dataset contains 400 classes of human actions and each class contains at least 400 clips. Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover 400/600/700 human action classes, depending on the dataset version. Mar 9, 2024 · I3D models pre-trained on Kinetics also placed first in the CVPR 2017 Charades challenge. Each clip Description: Kinetics: a large-scale human action dataset with 300000 videos clips in 400 classes. I contacted Kinetics Jun 21, 2021 · Kinetics 400, the first dataset developed, contains 400 classes and a minimum of 400 videos in each class. conda create -n YOUR_ENV_NAME pip python=3. We provide an analysis on how current architectures fare on the task of action classification on this dataset and how much performance improves on the smaller benchmark datasets Setup. 0. Unexpected token < in JSON at position 4. Similar to CIFAR-10/100-LT, it utilizes an imbalance factor to construct long-tailed variants of the MiniKinetics200 dataset. Apr 22, 2022 · 🐛 Describe the bug Error in downloading Kinetics 400 dataset. vv py bi xl oo iz sm wn tq ox