README.md

metadata

language: en
license: cc-by-4.0
task_categories:
  - image-classification
tags:
  - tinyML
  - open-images-v6
  - object-classification
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Bicycle&Motorcycle
            '1': Person
            '2': Chair
            '3': Cat
            '4': Houseplant
            '5': Table
            '6': Bottle
            '7': Dog
            '8': Glasses
            '9': Car
  splits:
    - name: calib_images/*
      num_examples: 640
    - name: test_images/*
      num_examples: 50
pretty_name: OpenImagesV6_small

Dataset Card for [OpenImagesV6_small]

This dataset is a custom downstream variant derived from the official Open Images V6 Dataset. It has been extracted for object classification applications in TinyML applications.

Dataset Description

• Curated by: [Omnivision Inc]
• Source Dataset: Open Images Dataset V6
• Language: English
• License: CC BY 4.0 (for annotations) / Flickr Terms of Use (for source images)

Licensing and Attribution Information ⚠️

This dataset features a split-licensing structure inheriting from its upstream source, Open Images V6:

1. Annotations: Any new or modified annotations, labels, and bounding boxes created for this project are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
2. Source Images: The underlying photographs are originating from Flickr. The creators of this dataset do not hold the copyright to these images. Use of the images is bound by the Flickr Terms of Use. Users are individually responsible for ensuring their compliance with the original photographers' terms, particularly regarding commercial downstream use.

Upstream Attribution

If you use this dataset, you must attribute both this derivative version and the original foundation dataset:

• Original Dataset Creators: Open Images (OpenImages: A public dataset for large-scale multi-label and multi-class image classification. (A. Kuzenetsova et al., 2017)).

Citation

If you use this dataset, please cite the following original paper alongside this repository:

@article{OpenImagesV4
  title={The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale},
  author={A. Kuznetsova, H. Rom, N. Alldrin, J. Uijlings, I. Krasin, J. Pont-Tuset, S. Kamali, S. Popov, M. Malloci, A. Kolesnikov, T. Duerig, and V. Ferrari},
  journal={International Journal of Computer Vision (IJCV)},
  year={2020}
}

@article{InstanceSegment
  title={Large-scale interactive object segmentation with human annotators},
  author={R. Benenson, S. Popov, and V. Ferrari},
  journal={Computer Vision and Pattern Recognition (CVPR)},
  year={2019}
}

@article{LocalizedNarratives
  title={Connecting Vision and Language with Localized Narratives},
  author={J. Pont-Tuset, J. Uijlings, S. Changpinyo, R. Soricut, and V. Ferrari},
  journal={European Conference on Computer Vision (ECCV)},
  year={2020}
}

@article{OpenImages
  title={OpenImages: A public dataset for large-scale multi-label and multi-class image classification},
  author={Krasin I., Duerig T., Alldrin N., Ferrari V., Abu-El-Haija S., Kuznetsova A., Rom H., Uijlings J., Popov S., Kamali S., Malloci M., Pont-Tuset J., Veit A., Belongie S., Gomes V., Gupta A., Sun C., Chechik G., Cai D., Feng Z., Narayanan D., Murphy K.},
  year={2017}
}