100+ datasets found
  1. P

    What is 91 club invite code? Dataset

    • paperswithcode.com
    Updated Apr 15, 2024
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    (2024). What is 91 club invite code? Dataset [Dataset]. https://paperswithcode.com/dataset/coco
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    Dataset updated
    Apr 15, 2024
    Description

    91 Club invite code is 4325118822517, which new users can enter during the registration process to unlock special rewards and welcome bonuses. By using this 91 Club invite code 4325118822517, players may receive extra wallet credits, deposit cashback, or referral perks that enhance their gaming experience right from the start. 91 Club is a growing online color prediction and gaming platform where users can play, predict, and win real money. The 91 Club invite code 4325118822517 acts as a gateway to exclusive promotional benefits and early access offers. Share this code with friends to earn referral commissions and increase your earnings while enjoying the games on 91 Club.

  2. R

    Coco Limited (person Only) Dataset

    • universe.roboflow.com
    zip
    Updated May 31, 2022
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    shreks swamp (2022). Coco Limited (person Only) Dataset [Dataset]. https://universe.roboflow.com/shreks-swamp/coco-dataset-limited--person-only
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 31, 2022
    Dataset authored and provided by
    shreks swamp
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    People Bounding Boxes
    Description

    COCO Dataset Limited (Person Only)

    ## Overview
    
    COCO Dataset Limited (Person Only) is a dataset for object detection tasks - it contains People annotations for 5,438 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  3. COCO, LVIS, Open Images V4 classes mapping

    • zenodo.org
    • data.niaid.nih.gov
    bin, csv, txt
    Updated Oct 13, 2022
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    Giuseppe Amato; Giuseppe Amato; Paolo Bolettieri; Paolo Bolettieri; Fabio Carrara; Fabio Carrara; Fabrizio Falchi; Fabrizio Falchi; Claudio Gennaro; Claudio Gennaro; Nicola Messina; Nicola Messina; Lucia Vadicamo; Lucia Vadicamo; Claudio Vairo; Claudio Vairo (2022). COCO, LVIS, Open Images V4 classes mapping [Dataset]. http://doi.org/10.5281/zenodo.7194300
    Explore at:
    csv, txt, binAvailable download formats
    Dataset updated
    Oct 13, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Giuseppe Amato; Giuseppe Amato; Paolo Bolettieri; Paolo Bolettieri; Fabio Carrara; Fabio Carrara; Fabrizio Falchi; Fabrizio Falchi; Claudio Gennaro; Claudio Gennaro; Nicola Messina; Nicola Messina; Lucia Vadicamo; Lucia Vadicamo; Claudio Vairo; Claudio Vairo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This repository contains a mapping between the classes of COCO, LVIS, and Open Images V4 datasets into a unique set of 1460 classes.

    COCO [Lin et al 2014] contains 80 classes, LVIS [gupta2019lvis] contains 1460 classes, Open Images V4 [Kuznetsova et al. 2020] contains 601 classes.

    We built a mapping of these classes using a semi-automatic procedure in order to have a unique final list of 1460 classes. We also generated a hierarchy for each class, using wordnet

    This repository contains the following files:

    • coco_classes_map.txt, contains the mapping for the 80 coco classes
    • lvis_classes_map.txt, contains the mapping for the 1460 coco classes
    • openimages_classes_map.txt, contains the mapping for the 601 coco classes
    • classname_hyperset_definition.csv, contains the final set of 1460 classes, their definition and hierarchy
    • all-classnames.xlsx, contains a side-by-side view of all classes considered

    This mapping was used in VISIONE [Amato et al. 2021, Amato et al. 2022] that is a content-based retrieval system that supports various search functionalities (text search, object/color-based search, semantic and visual similarity search, temporal search). For the object detection VISIONE uses three pre-trained models: VfNet [Zhang et al. 2021] (trained on COCO dataset), Mask R-CNN [He et al. 2017] (trained on LVIS), and a Faster R-CNN+Inception ResNet (trained on the Open Images V4).

    This is repository is released under a Creative Commons Attribution license, please cite the following paper if you use it in your work in any form:

    @inproceedings{amato2021visione,
     title={The visione video search system: exploiting off-the-shelf text search engines for large-scale video retrieval},
     author={Amato, Giuseppe and Bolettieri, Paolo and Carrara, Fabio and Debole, Franca and Falchi, Fabrizio and Gennaro, Claudio and Vadicamo, Lucia and Vairo, Claudio},
     journal={Journal of Imaging},
     volume={7},
     number={5},
     pages={76},
     year={2021},
     publisher={Multidisciplinary Digital Publishing Institute}
    }
    

    References:

    [Amato et al. 2022] Amato, G. et al. (2022). VISIONE at Video Browser Showdown 2022. In: , et al. MultiMedia Modeling. MMM 2022. Lecture Notes in Computer Science, vol 13142. Springer, Cham. https://doi.org/10.1007/978-3-030-98355-0_52

    [Amato et al. 2021] Amato, G., Bolettieri, P., Carrara, F., Debole, F., Falchi, F., Gennaro, C., Vadicamo, L. and Vairo, C., 2021. The visione video search system: exploiting off-the-shelf text search engines for large-scale video retrieval. Journal of Imaging, 7(5), p.76.

    [Gupta et al.2019] Gupta, A., Dollar, P. and Girshick, R., 2019. Lvis: A dataset for large vocabulary instance segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 5356-5364).

    [He et al. 2017] He, K., Gkioxari, G., Dollár, P. and Girshick, R., 2017. Mask r-cnn. In Proceedings of the IEEE international conference on computer vision (pp. 2961-2969).

    [Kuznetsova et al. 2020] Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Kolesnikov, A. and Duerig, T., 2020. The open images dataset v4. International Journal of Computer Vision, 128(7), pp.1956-1981.

    [Lin et al. 2014] Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P. and Zitnick, C.L., 2014, September. Microsoft coco: Common objects in context. In European conference on computer vision (pp. 740-755). Springer, Cham.

    [Zhang et al. 2021] Zhang, H., Wang, Y., Dayoub, F. and Sunderhauf, N., 2021. Varifocalnet: An iou-aware dense object detector. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 8514-8523).

  4. R

    Microsoft Coco Dataset

    • universe.roboflow.com
    zip
    Updated Apr 4, 2025
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    Microsoft (2025). Microsoft Coco Dataset [Dataset]. https://universe.roboflow.com/microsoft/coco/model/3
    Explore at:
    zipAvailable download formats
    Dataset updated
    Apr 4, 2025
    Dataset authored and provided by
    Microsoft
    Variables measured
    Object Bounding Boxes
    Description

    Microsoft Common Objects in Context (COCO) Dataset

    The Common Objects in Context (COCO) dataset is a widely recognized collection designed to spur object detection, segmentation, and captioning research. Created by Microsoft, COCO provides annotations, including object categories, keypoints, and more. The model it a valuable asset for machine learning practitioners and researchers. Today, many model architectures are benchmarked against COCO, which has enabled a standard system by which architectures can be compared.

    While COCO is often touted to comprise over 300k images, it's pivotal to understand that this number includes diverse formats like keypoints, among others. Specifically, the labeled dataset for object detection stands at 123,272 images.

    The full object detection labeled dataset is made available here, ensuring researchers have access to the most comprehensive data for their experiments. With that said, COCO has not released their test set annotations, meaning the test data doesn't come with labels. Thus, this data is not included in the dataset.

    The Roboflow team has worked extensively with COCO. Here are a few links that may be helpful as you get started working with this dataset:

  5. h

    coco2017

    • huggingface.co
    • opendatalab.com
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    Padilla, coco2017 [Dataset]. https://huggingface.co/datasets/rafaelpadilla/coco2017
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Authors
    Padilla
    Description

    This dataset contains all COCO 2017 images and annotations split in training (118287 images) and validation (5000 images).

  6. P

    COCO Captions Dataset

    • paperswithcode.com
    • opendatalab.com
    Updated Oct 4, 2022
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    Xinlei Chen; Hao Fang; Tsung-Yi Lin; Ramakrishna Vedantam; Saurabh Gupta; Piotr Dollar; C. Lawrence Zitnick (2022). COCO Captions Dataset [Dataset]. https://paperswithcode.com/dataset/coco-captions
    Explore at:
    Dataset updated
    Oct 4, 2022
    Authors
    Xinlei Chen; Hao Fang; Tsung-Yi Lin; Ramakrishna Vedantam; Saurabh Gupta; Piotr Dollar; C. Lawrence Zitnick
    Description

    COCO Captions contains over one and a half million captions describing over 330,000 images. For the training and validation images, five independent human generated captions are be provided for each image.

  7. P

    COCO-WholeBody Dataset

    • paperswithcode.com
    Updated Oct 9, 2022
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    Sheng Jin; Lumin Xu; Jin Xu; Can Wang; Wentao Liu; Chen Qian; Wanli Ouyang; Ping Luo (2022). COCO-WholeBody Dataset [Dataset]. https://paperswithcode.com/dataset/coco-wholebody
    Explore at:
    Dataset updated
    Oct 9, 2022
    Authors
    Sheng Jin; Lumin Xu; Jin Xu; Can Wang; Wentao Liu; Chen Qian; Wanli Ouyang; Ping Luo
    Description

    COCO-WholeBody is an extension of COCO dataset with whole-body annotations. There are 4 types of bounding boxes (person box, face box, left-hand box, and right-hand box) and 133 keypoints (17 for body, 6 for feet, 68 for face and 42 for hands) annotations for each person in the image.

  8. R

    Vehicles Coco Dataset

    • universe.roboflow.com
    zip
    Updated Jan 23, 2022
    + more versions
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    Vehicle MSCOCO (2022). Vehicles Coco Dataset [Dataset]. https://universe.roboflow.com/vehicle-mscoco/vehicles-coco/dataset/1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jan 23, 2022
    Dataset authored and provided by
    Vehicle MSCOCO
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Vehicles Bounding Boxes
    Description

    Vehicles Coco

    ## Overview
    
    Vehicles Coco is a dataset for object detection tasks - it contains Vehicles annotations for 18,998 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  9. h

    depth_coco

    • huggingface.co
    Updated Jul 11, 2024
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    Neil de la fuente (2024). depth_coco [Dataset]. http://doi.org/10.57967/hf/2704
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 11, 2024
    Authors
    Neil de la fuente
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    Dataset Card for MS COCO Depth Maps

    This dataset is a collection of depth maps generated from the MS COCO dataset images using the Depth-Anything-V2 model, along with the original MS COCO images.

      Dataset Details
    
    
    
    
    
      Dataset Description
    

    This dataset contains depth maps generated from the MS COCO (Common Objects in Context) dataset images using the Depth-Anything-V2 model. It provides depth information for each image in the original MS COCO dataset, offering a new… See the full description on the dataset page: https://huggingface.co/datasets/neildlf/depth_coco.

  10. a

    MS Common Objects in Context (COCO2014)

    • academictorrents.com
    bittorrent
    Updated Oct 9, 2015
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    Microsoft (2015). MS Common Objects in Context (COCO2014) [Dataset]. https://academictorrents.com/details/f993c01f3c268b5d57219a38f8ec73ee7524421a
    Explore at:
    bittorrent(26815885986)Available download formats
    Dataset updated
    Oct 9, 2015
    Dataset authored and provided by
    Microsoft
    License

    https://academictorrents.com/nolicensespecifiedhttps://academictorrents.com/nolicensespecified

    Description

    Microsoft COCO is a new image recognition, segmentation, and captioning dataset. Microsoft COCO has several features: Object segmentation Recognition in Context Multiple objects per image More than 300,000 images More than 2 Million instances 80 object categories 5 captions per image The 2014 Testing Images are for the MS COCO Captioning Challenge, while the 2015 Testing Images are for the MS COCO Detection Challenge. The train and val data are common to both challenges. Note also that as an alternative to downloading the large image zip files, individual images may be downloaded from the COCO website using the "coco_url" field specified in the image info struct.

  11. P

    COCO-Text Dataset

    • paperswithcode.com
    Updated May 6, 2024
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    Andreas Veit; Tomas Matera; Lukas Neumann; Jiri Matas; Serge Belongie (2024). COCO-Text Dataset [Dataset]. https://paperswithcode.com/dataset/coco-text
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    Dataset updated
    May 6, 2024
    Authors
    Andreas Veit; Tomas Matera; Lukas Neumann; Jiri Matas; Serge Belongie
    Description

    The COCO-Text dataset is a dataset for text detection and recognition. It is based on the MS COCO dataset, which contains images of complex everyday scenes. The COCO-Text dataset contains non-text images, legible text images and illegible text images. In total there are 22184 training images and 7026 validation images with at least one instance of legible text.

  12. R

    Tiny Coco Dataset

    • universe.roboflow.com
    zip
    Updated Nov 23, 2024
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    mda (2024). Tiny Coco Dataset [Dataset]. https://universe.roboflow.com/mda-3nug1/tiny-coco-gilct
    Explore at:
    zipAvailable download formats
    Dataset updated
    Nov 23, 2024
    Dataset authored and provided by
    mda
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Coco Objects Bounding Boxes
    Description

    Tiny COCO

    ## Overview
    
    Tiny COCO is a dataset for object detection tasks - it contains Coco Objects annotations for 5,025 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  13. Coco 128 Dataset

    • universe.roboflow.com
    zip
    Updated Sep 28, 2021
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    Team Roboflow (2021). Coco 128 Dataset [Dataset]. https://universe.roboflow.com/team-roboflow/coco-128/dataset/2
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    zipAvailable download formats
    Dataset updated
    Sep 28, 2021
    Dataset provided by
    Roboflowhttps://roboflow.com/
    Authors
    Team Roboflow
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Common Objects Bounding Boxes
    Description

    COCO 128 is a subset of 128 images of the larger COCO dataset. It reuses the training set for both validation and testing, with the purpose of proving that your training pipeline is working properly and can overfit this small dataset.

    COCO 128 is a great dataset to use the first time you are testing out a new model.

  14. P

    COCO-CN Dataset

    • paperswithcode.com
    • opendatalab.com
    • +1more
    Updated Nov 6, 2024
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    Xirong Li; Chaoxi Xu; Xiaoxu Wang; Weiyu Lan; Zhengxiong Jia; Gang Yang; Jieping Xu (2024). COCO-CN Dataset [Dataset]. https://paperswithcode.com/dataset/coco-cn
    Explore at:
    Dataset updated
    Nov 6, 2024
    Authors
    Xirong Li; Chaoxi Xu; Xiaoxu Wang; Weiyu Lan; Zhengxiong Jia; Gang Yang; Jieping Xu
    Description

    COCO-CN is a bilingual image description dataset enriching MS-COCO with manually written Chinese sentences and tags. The new dataset can be used for multiple tasks including image tagging, captioning and retrieval, all in a cross-lingual setting.

  15. h

    cocostuff

    • huggingface.co
    • opendatalab.com
    Updated Apr 20, 2023
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    Shunsuke Kitada (2023). cocostuff [Dataset]. https://huggingface.co/datasets/shunk031/cocostuff
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    Dataset updated
    Apr 20, 2023
    Authors
    Shunsuke Kitada
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    COCO-Stuff augments all 164K images of the popular COCO dataset with pixel-level stuff annotations. These annotations can be used for scene understanding tasks like semantic segmentation, object detection and image captioning.

  16. R

    Stop Sign Detection With Coco Dataset

    • universe.roboflow.com
    zip
    Updated Oct 28, 2023
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    Szchenyi Istvn Egyetem (2023). Stop Sign Detection With Coco Dataset [Dataset]. https://universe.roboflow.com/szchenyi-istvn-egyetem/stop-sign-detection-with-coco
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 28, 2023
    Dataset authored and provided by
    Szchenyi Istvn Egyetem
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Stopsign 73Rz Bounding Boxes
    Description

    Stop Sign Detection With COCO

    ## Overview
    
    Stop Sign Detection With COCO is a dataset for object detection tasks - it contains Stopsign 73Rz annotations for 3,161 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  17. F

    SlideImages

    • data.uni-hannover.de
    • service.tib.eu
    tar, zip
    Updated Jan 20, 2022
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    TIB (2022). SlideImages [Dataset]. https://data.uni-hannover.de/dataset/slideimages
    Explore at:
    tar(1360140103), zip(107220518)Available download formats
    Dataset updated
    Jan 20, 2022
    Dataset authored and provided by
    TIB
    License

    Attribution-ShareAlike 3.0 (CC BY-SA 3.0)https://creativecommons.org/licenses/by-sa/3.0/
    License information was derived automatically

    Description

    Please note: this archive requires support for dangling symlinks, which excludes the Windows operating system.

    To use this dataset, you will need to download the MS COCO 2017 detection images and expand them to a folder called coco17 in the train_val_combined directory. The download can be found here: https://cocodataset.org/#download You will also need to download the AI2D image description dataset and expand them to a folder called ai2d in the train_val_combined directory. The download can be found here: https://prior.allenai.org/projects/diagram-understanding

    License Notes for Train and Val: Since the images in this dataset come from different sources, they are bound by different licenses.

    Images for bar charts, x-y plots, maps, pie charts, tables, and technical drawings were downloaded directly from wikimedia commons. License and authorship information is stored independently for each image in these categories in the wikimedia_commons_licenses.csv file. Each row (note: some rows are multi-line) is formatted so:

    Images in the slides category were taken from presentations which were downloaded from Wikimedia Commons. The names of the presentations on Wikimedia Commons omits the trailing underscore, number, and file extension, and ends with .pdf instead. The source materials' licenses are shown in source_slices_licenses.csv.

    Wikimedia commons photos' information page can be found at "https://commons.wikimedia.org/wiki/File:

    License Notes for Testing: The testing images have been uploaded to SlideWiki by SlideWiki users. The image authorship and copyright information is available in authors.csv.

    Further information can be found for each image using the SlideWiki file service. Documentation is available at https://fileservice.slidewiki.org/documentation#/ and in particular: metadata is available at "https://fileservice.slidewiki.org/metadata/

    This is the SlideImages dataset, which has been assembled for the SlideImages paper. If you find the dataset useful, please cite our paper: https://doi.org/10.1007/978-3-030-45442-5_36

  18. E

    SPEECH-COCO

    • live.european-language-grid.eu
    audio wav
    Updated Dec 10, 2023
    + more versions
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    (2023). SPEECH-COCO [Dataset]. https://live.european-language-grid.eu/catalogue/corpus/7686
    Explore at:
    audio wavAvailable download formats
    Dataset updated
    Dec 10, 2023
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Introduction: Our corpus is an extension of the MS COCO image recognition and captioning dataset. MS COCO comprises images paired with a set of five captions. Yet, it does not include any speech. Therefore, we used Voxygen's text-to-speech system to synthesise the available captions. The addition of speech as a new modality enables MSCOCO to be used for researches in the field of language acquisition, unsupervised term discovery, keyword spotting, or semantic embedding using speech and vision. Our corpus is licensed under a Creative Commons Attribution 4.0 License. Data Set: This corpus contains 616,767 spoken captions from MSCOCO's val2014 and train2014 subsets (respectively 414,113 for train2014 and 202,654 for val2014). We used 8 different voices. 4 of them have a British accent (Paul, Bronwen, Judith, and Elizabeth) and the 4 others have an American accent (Phil, Bruce, Amanda, Jenny). In order to make the captions sound more natural, we used SOX tempo command, enabling us to change the speed without changing the pitch. 1/3 of the captions are 10% slower than the original pace, 1/3 are 10% faster. The last third of the captions was kept untouched. We also modified approximately 30% of the original captions and added disfluencies such as "um", "uh", "er" so that the captions would sound more natural. Each WAV file is paired with a JSON file containing various information: timecode of each word in the caption, name of the speaker, name of the WAV file, etc. The JSON files have the following data structure: {"duration": float, "speaker": string, "synthesisedCaption": string, "timecode": list, "speed": float, "wavFilename": string, "captionID": int, "imgID": int, "disfluency": list}. On average, each caption comprises 10.79 tokens, disfluencies included. The WAV files are on average 3.52 seconds long.

  19. R

    Coco Person Dataset

    • universe.roboflow.com
    zip
    Updated Mar 24, 2025
    + more versions
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    dataset (2025). Coco Person Dataset [Dataset]. https://universe.roboflow.com/dataset-uutxr/coco-person-gi27a
    Explore at:
    zipAvailable download formats
    Dataset updated
    Mar 24, 2025
    Dataset authored and provided by
    dataset
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Variables measured
    Coco Person Bounding Boxes
    Description

    Coco Person

    ## Overview
    
    Coco Person is a dataset for object detection tasks - it contains Coco Person annotations for 5,081 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [MIT license](https://creativecommons.org/licenses/MIT).
    
  20. Microsoft Coco 2017 Dataset

    • universe.roboflow.com
    zip
    Updated Jan 4, 2022
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    Roboflow Public (2022). Microsoft Coco 2017 Dataset [Dataset]. https://universe.roboflow.com/roboflow-public/microsoft-coco-2017-dataset
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    zipAvailable download formats
    Dataset updated
    Jan 4, 2022
    Dataset provided by
    Roboflowhttps://roboflow.com/
    Authors
    Roboflow Public
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Coco Objects Bounding Boxes
    Description

    Microsoft COCO 2017 Dataset

    ## Overview
    
    Microsoft COCO 2017 Dataset is a dataset for object detection tasks - it contains Coco Objects annotations for 2,245 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
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(2024). What is 91 club invite code? Dataset [Dataset]. https://paperswithcode.com/dataset/coco

What is 91 club invite code? Dataset

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33 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 15, 2024
Description

91 Club invite code is 4325118822517, which new users can enter during the registration process to unlock special rewards and welcome bonuses. By using this 91 Club invite code 4325118822517, players may receive extra wallet credits, deposit cashback, or referral perks that enhance their gaming experience right from the start. 91 Club is a growing online color prediction and gaming platform where users can play, predict, and win real money. The 91 Club invite code 4325118822517 acts as a gateway to exclusive promotional benefits and early access offers. Share this code with friends to earn referral commissions and increase your earnings while enjoying the games on 91 Club.

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