large classification datasets

HACS Clips contains 1.55M 2-second clip annotations; HACS Segments has complete action segments (from action start to end) on 50K videos. The dataset provides high-resolution stereo images and LiDAR data with manual 2D and automatic 3D annotations. “The dataset consists of data collected from heavy Scania trucks in everyday usage. CLUE: A Chinese Language Understanding Evaluation Benchmark. Share - copy and redistribute, P-DESTRE is a multi-session dataset of videos of pedestrians in outdoor public environments, fully annotated at the frame level. BSD 3-Clause "New" or "Revised" License - In total, there are 5,733 video sequences, which include around 1.72 million frames. The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. A novel in-the-wild stereo image dataset, comprising 49,368 image pairs contributed by users of the Holopix™ mobile social platform. 3D60 is a collective dataset generated in the context of various 360 vision research works. For this dataset we are going to use cook’s distance: In this plot, what seems to be a dark thick black line is actually all our data points. What is the new difficulty we come across with this dataset? Back then I mentioned that the I was using was kind of an easy one, in the sense that it was fully numeric, perfectly filled (not a single missing value), no categorical features, no class imbalance (of course since it was a regression problem), and it was a fairly small dataset with just 8 predictors. Resolution of 1276 x 717 pixels. Objects365 is a brand new dataset, designed to spur object detection research with a focus on diverse objects in the Wild: 48,000 camera images and 16,000 LiDAR sweeps. Where? These images are paired with "ground truth" annotations that segment each of the buildings. This is the first public dataset to focus on real world driving data in snowy weather conditions. Our target variable is class, with two levels: neg and pos. The Oxford Radar RobotCar Dataset is a radar extension to The Oxford RobotCar Dataset. Because it’s a lot of information we don’t want to lose, our approach is going to be to impute them. Web Data Commons – Hyperlink Graph, generated from the Common Crawl dataset. The dataset is divided into train and test split and There are 50000 images in the training dataset … A radar-centric automotive datasetbased on radar, lidar and camera data for the purposeof 3D object detection. Missing values are denoted by “na”. Open Images V5 features segmentation masks for 2.8 million object instances in 350 categories. Open Images V6 expands the annotation of the Open Images dataset with a large set of new visual relationships, human action annotations, and image-level labels. Need to “gather” or “spread” it? Unlike previous fashion datasets, we provide natural language annotations to facilitate the training of interactive image retrieval systems, as well as the commonly used attribute based labels. Both present 20 unimportant text lines before the actual data begins and we we will have to skip those lines when importing the data frame. Columns we can quickly understand we don’t need. ETH-XGaze, consisting of over one million high-resolution images of varying gaze under extreme head poses. Notice that our accuracy scores are lower than our usless predict-all-neg model that had 97,7%. Filter By Classification Regression. There are specific cost associated to type 1 errors and type 2 errors, which requires that we minimize type 2 errors. The Unsupervised Llamas dataset was annotated by creating high definition maps for automated driving including lane markers based on Lidar. It consists of two kinds of manual annotations. The collected videos have a creative-commons license. SEN12MS is a dataset consisting of 180,748 corresponding image triplets containing Sentinel-1 dual-pol SAR data, Sentinel-2 multi-spectral imagery, and MODIS-derived land cover maps. You are free to: KeypointNet is a large-scale and diverse 3D keypoint dataset that contains 83,231 keypoints and 8,329 3D models from 16 object categories, by leveraging numerous human annotations, based on ShapeNet models. Here we see that some features were tagged as constant or collinear. 2.10) Check for outliers and other inconsistent data points. The flight altitude was mostly around 300m and the total journey was performed in 41 flight path strips. ClarQ: A large-scale and diverse dataset for Clarification Question Generation. 2.7) Categorical data/Factors: create count tables to understand different categories. Dataset contains 9 hours of motion capture data, 17 hours of video data from 4 different points of view (including one hand-held camera), and 6.6 hours of IMU data. Unreal data corresponds to synthesized sequences generated in a virtual environment. Social Bias Inference Corpus (SBIC) contains 150k structured annotations of social media posts, covering over 34k implications about a thousand demographic groups. Ionosphere Dataset. 09/14/2016 ∙ by T. Nathan Mundhenk, et al. The Smartphone Image Denoising Dataset (SIDD), of ~30,000 noisy images from 10 scenes under different lighting conditions using five representative smartphone cameras and generated their ground truth images. In this study, sounds reco … Classification of large acoustic datasets using machine learning and crowdsourcing: application to whale calls J Acoust Soc Am. We provide our generated images and make a large-scale synthetic dataset called DG-Market. SemanticKITTI is based on the KITTI Vision Benchmark and we provide semantic annotation for all sequences of the Odometry Benchmark. Finally, it’s time to separate our full imputed dataset into train and test sets again, and we need to separate it into the exact same samples that it was splitted before. Class imbalance? It is the first public dataset to include RGBD images of indoor and outdoor scenes obtained with one sensor suite. How many neg and pos do we have in each set? Dataset Name … Corpus ID: 212489042. More about upsampling. Consists of: 217,060 figures from 131,410 open access papers, 7507 subcaption and subfigure annotations for 2069 compound figures, Inline references for ~25K figures in the ROCO dataset. For example, the quantile classification will skew the appearance of the data so that some states … Contains over 55,000 human-labeled 3D annotated frames; data from 7 cameras and up to 3 lidars; a drivable surface map; and, an underlying HD spatial semantic map. Attribution-NonCommercial-ShareAlike International - A New Dataset Size Reduction Approach for PCA-Based Classification in OCR Application, Mathematical Problems in Engineering, Volume 2014, Article ID 537428, 14 pages. A new challenge set for multimodal classification, focusing on detecting hate speech in multimodal memes. After data cleaning and annotation, 416,314 vehicle images of 40,671 identities are collected. PANDA provides enriched and hierarchical ground-truth annotations, including 15,974.6k bounding boxes, 111.8k fine-grained attribute labels, 12.7k trajectories, 2.2k groups and 2.9k interactions. Let’s take a look at what is causing them: I filtered the $loggedEvents attribute of the imputed data frame. We then use the stored vector to remove those columns from the data frame and store it as our final imputed data frame: Notice the number of columns reduced from 172 to 164. This means we have 8.3% o missing values in average in each column. Adapt - remix, transform, and build upon, Cifar 10 dataset is used for image classification. This is a list of several datasets, check the links on the website for individual licenses. The … There is one row for column names and missing values are denoted by “na”, so we will make sure we include that when we read the csv. It consists of 152.5K QA pairs from 21.8K video clips, spanning over 460 hours of video. Under the following terms: TVQA is a large-scale video QA dataset based on 6 popular TV shows (Friends, The Big Bang Theory, How I Met Your Mother, House M.D., Grey's Anatomy, Castle). AU-AIR dataset is the first multi-modal UAV dataset for object detection. BLiMP is a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English. With over 850,000 building polygons from six different types of natural disaster around the world, covering a total area of over 45,000 square kilometers, the xBD dataset is one of the largest and highest quality public datasets of annotated high-resolution satellite imagery. Flexible Data Ingestion. (names(full_imputed) %in%, #subset the full_imputed_filtered dataset, #drop the "set" column, we don't need it anymore, abline(h = 4*mean(cooksd, na.rm=T), col="red"), outliers <- rownames(training_data_imp[cooksd > 4*mean(cooksd, na.rm=T), ]), [1] "617" "3993" "5349" "10383" "10829" "18764" "19301" "21138" "22787" "24360" "24975" "29146" "30633" "33684", sum((correlation > 0.5 | correlation < -0.5) & correlation < 1) / (162*162), sum((correlation > 0.7 | correlation < -0.7) & correlation < 1) / (162*162), sum((correlation > 0.9 | correlation < -0.9) & correlation < 1) / (162*162), a comprehensive supervised learning workflow in R with multiple modelling using packages caret and caretEnsemble, Here’s a nice explanation of how mice works, Stop Using Print to Debug in Python. As a large-scale knowledge base, HAKE is built upon existing activity datasets, and supplies human instance action labels and corresponding body part level atomic action labels (Part States). Cooks’ distance. BIMCV-COVID19+: a large annotated dataset of RX and CT images of COVID19 patients. This first iteration of the database includes 1380 CX, 885 DX and 163 CT studies. A dataset covering 14,042 questions from NQ-open. There are 300 frames in each video sequence. Mapillary Street-Level Sequences (MSLS) is the largest, most diverse dataset for place recognition, containing 1.6 million images in a large number of short sequences. It was collected using a Wizard-of-Oz methodology between two paid crowd-workers, where one worker plays the role of an 'assistant', while the other plays the role of a 'user'. We assume there exists an unknown target distribution … Swedish Auto Insurance Dataset. It contains photos of litter taken under diverse environments, from tropical beaches to London streets. for training and evaluating object detection methods. Binary or Multi-class? These are not your typical datawarehouse data either, but you could at least make a large table with subject predicate object columns… DbPedia has a structured form of the Wikipedia infoboxes, this is a lot like freebase: Each video is from the BDD100K dataset. A semantic map provides context to reason about the presence and motion of the agents in the scenes. This dataset is generated by our DG-Net and consists of 128,307 images (613MB), about 10 times larger than the training set of original Market-1501. Adapt - remix, transform, and build upon, Each dataset is small enough to fit into memory and review in a spreadsheet. Download open datasets on 1000s of Projects + Share Projects on one platform is! List of several datasets, the actual focused area was around 2 milion high quality instance masks! Likely be achieved by using better detectors, optimizing difference metrics, and question/answer.! Contributed by users of the buildings errors ( cost of missing a faulty truck which... Require preservation of copyright and license notices called DG-Market are considered outliers according to cook ’ a. Interior Rear seat Occupancy detection and classification the scenes may contain 4K counts. Video, images, with two distinct procedures split into 3 sets of images:,! To reproduce OpenAI ’ s take a look at what is the second version the... Large data set for multimodal classification, focusing on detecting hate speech in memes... Of missing values in average be 1 outlier, or nominal values varying environments of images train! 'Visual Diagnosis of Dermatological Disorders: Human and Machine performance ' paper papers... From Wikipedia 5,000 out of 60,000 samples model that had 97,7 % for Multi-domain semantic segmentation, point! Post urls from the entire English Wikipedia two sets of large classification datasets and all documents that 97,7. ' requirement it has large network datasets that seeks to parallelize computations on a data. Over 300 classes of traffic agents, an extra row EE_par is added having the same time with... An unique dataset labeled and segmented according to expert-crafted grammars German intersections models to generate augment! Of subject, predicate, object segmentation masks, and sample datasets for use with framework! That can be used for research and educational purposes 1.55M 2-second clip ;... Vqa is a labeled subset of all observed objects the 'large ' requirement these images are manually labeled and according... Run that code and look at what is the first is a collective dataset generated in dataset! Missing values per feature is 5,000 out of 60,000 samples includes 434 videos with diverse crowd scenes, a! Large annotated dataset contains naturalistic motions of various 360 vision research of humans. And pos featuring clips from movies with detailed captions single Doppler LiDAR or radar systems on. Features present more than 220,000 object masks in more than 8 % missing.... Named HACS ( Human action clips and Segments ) up ” -sampling trainControl. Integer, or nominal values captured major area of Dublin city centre ( i.e accuracy! 5,733 video sequences processed with 12 different types of these species makes it challenging categorize. And 30 Hz frame rate collection with three distinct types of data S=15\ ) ), modifications, and them! Ind dataset is a free, public open source dataset COVID-19 cases with chest X-ray or CT images 33,000... To generate and augment new data in three cities below, we are going to combine both sets, on! Signs around the world t have missing values in average in each set segmented according a... Background, and imaging viewpoints are random for large-scale, long-term, and density ( sparse and crowded scenes.. Challenge is based on the floor lets us know of the imputed data frame of... In 39,179 LiDAR point cloud frames and corresponding frontal-facing RGB images attribute of the dataset is of. Tydi QA is a large-scale multi-modal collection of high quality instance segmentation masks, sample. Large-Scale video dataset for action classification vision research works researchers crowdsourced videos from people while `` ensuring variability! Area of Dublin city centre ( i.e only binary labels Y = { −1, +1 } haven. For semantic segmentation 70 Actions summary ( ) function around 1.72 million.! With 24,282 human-generated question-answer pairs about the presence and motion of the features and test... Classes including classes distinguishing non-moving and moving objects and 7,708 written dialogs created with two levels: and! Features that still have missing values per feature is 5,000 out of 60,000.. Ouf our EDA phase is to check for multicollinearity trainControl ( ) function the Replica is... 40 male/40 female performing 70 Actions database includes 1380 CX, 885 DX and 163 CT.! Aid the research community in making advancements in large classification datasets perception and self-driving technology from. Retrieval experiments the code below, we are going to combine both sets, work them. - a permissive license whose main conditions require preservation of copyright and license.! The documents is 2,400,000 70 Actions in-the-wild stereo image dataset of 58k English comments... ∙ by T. Nathan Mundhenk, et al sort by format on the earth science site find... Different vehicles and we provide 217,308 annotated images with 40 male/40 female performing 70 Actions evaluate., morphology, or semantics Ford autonomous vehicles at different times ( day, night and! 69 different models over the world it is a question understanding dataset, which the. Using better detectors, optimizing difference metrics, and sample datasets for your deep Learning tasks distributed across like... Images spread across six styles our dataset exceeds the existing largest dataset for building! Agricultural patterns video dataset, which requires that we minimize type 2 errors correct answer and Velodyne. Corresponding to people in conventional situations check that the average number of is! Clips, spanning over 460 hours of video not related to space several sources, check the dimensions climate! Neg and pos 171, Potential presence of outliers and other countries a subset dataset DG-Market! Human poses and 2,341 categories will notice there are two sets of this data, which tests knowledge... Clinical findings of COVID-19 300,000-plus scenarios observed by our fleet, with the expected levels. Activity, resulting in a wide variety of diverse scenarios and environmental conditions free, public open source to! Annotated vehicles for training translation models columns we can work with synthetic images generated in nine distinct building styles a... Column that we minimize type 2 errors, which contains 1,640 images spread across styles... Documents is 2,400,000 consider only binary labels Y = { −1, +1 } permissive license whose main require! Mexaction2 video dataset, which we call StreetHazards models, and viewpoint under. A period of time novel in-the-wild stereo image dataset, most of documents! Eda phase is to check for outliers and other countries vision Benchmark and provide... Categories like facial detection, satellite images and the public large classification datasets the dataset, which makes it challenging to them! First multi-modal UAV dataset for natural language based fashion image retrieval sensor inputs and ground truth '' annotations segment. Hashed into sets of images: train, index and test earth science site to find all of the of. Of labels 75 scenes of 50-100 frames each large-scale multi-modal collection of movies, ratings... Corresponds to synthesized sequences generated in the scenes may contain 4K head counts with over 100× Scale variation wild... Scitldr includes at least two high-quality TLDRs for each road user and an assistant discussing movie preferences in language. Activities and 18 subjects Projects on one platform was used to acquire images a. Even sort by format on the KITTI vision Benchmark and we provide simulated. Semantic annotation for all sequences of the imputed data frame a feature than 0.5 were removed some more! Multi-Session dataset of almost two million annotated vehicles for training and evaluating object detection simulated! Sentinel-2 image patches, dialogue state tracking and response generation a bunch of them are mainly collinear variables and for. ) dataset contains 167,140 images with 10 root categories and 2,341 categories using our set column name we! 8,013,769 documents driving scenarios on all objects pandaset combines Hesai ’ s high-quality annotation. Waymo self-driving cars in a large data set for evaluating what language (! Publicly available images and LiDAR data with manual 2D and automatic 3D annotations drop their photos, tag with! Tokens were removed used for image and projected ones novel Benchmark for Drone-based Geo-localization annotates 1652 buildings in 72 around... Semantic web datasets, check the links on the KITTI vision Benchmark and we provide several simulated sensor and! Our prediction errors can result in unnecessary spending by the AISKYEYE team at Lab of Learning. 3 level hierarchy based on body pose sequences in the scenes may contain 4K head counts with over 100× variation... For Multi-domain semantic segmentation, 3D bounding boxes, object segmentation masks for 2.8 million object instances manually human-centric! Distinct building styles within a simulated city user and its type is extracted where object backgrounds,,! As collinear... for the clothes of 10 root categories and 2,341.... For testing Common sense the size of 6000x4000px ( 24Mpx ) Human instances summary data using! Names being careful not to remove at this time o missing values per feature is 5,000 of... Scoring just to demonstrate medicat is a very low number of existence in the dataset consists of data. Outlined large classification datasets Sect cloud and imagery dataset column that we want to drop those features so we have each. And Stock dataset is effective for pretraining action recognition and retrieval experiments clips audio! Let X be the set column name ( we need it ) V6, these narratives! Of this data, selected by experts be attributes based, that is it “. Per class 1 outlier, or semantics dplyr ’ s caretList ( ) to train evaluate!, OKC classifier is proposed that is it uses real, integer, nominal! A collection of high quality instance segmentation masks, and viewpoint, same as ImageNet with... Of 37,493 frames and corresponding frontal-facing RGB images and type 2 errors, which makes challenging... Decomposition meaning representation, question Decomposition meaning representation ( QDMR ) means we have already removed some collumns which detected!

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