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---
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license: apache-2.0
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task_categories:
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- image-text-to-text
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tags:
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- image
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language:
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- en
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size_categories:
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- 1M<n<10M
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train/*
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- split: valid
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path: data/validation/*
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- split: test
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path: data/test/*
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---
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# Open Images V7 + Narratives
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[Original Source](https://storage.googleapis.com/openimages/web/index.html) | [Google Localized Narrative](https://google.github.io/localized-narratives/)
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## 📌 Introduction
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This dataset collects the images and annotations from the original Open Images Dataset V7 and the annotations from the project [localized-narratives](https://github.com/google/localized-narratives).
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Out of the 9M images, a subset of 1.9M images have been annotated with: bounding boxes, object segmentations, visual relationships, localized narratives, point-level labels, and image-level labels. (The remaining images have only image-level labels).
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## 🙏 Acknowledgement
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All credits to the original Open Images Dataset V7 and the localized-narratives teams.
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## 📜 Cite
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Please consider to cite the following related papers:
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1. ["Extreme clicking for efficient object annotation"](https://arxiv.org/abs/1708.02750), Papadopolous et al., ICCV 2017.
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2. ["We don't need no bounding-boxes: Training object class detectors using only human verification"](https://arxiv.org/abs/1602.08405), Papadopolous et al., CVPR 2016.
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3. ["The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale"](https://arxiv.org/abs/1811.00982), Kuznetsova et al., arXiv:1811.00982 2018.
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4. ["Large-scale interactive object segmentation with human annotators"](https://arxiv.org/pdf/1903.10830), Benenson et al., CVPR 2019.
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5. ["Natural Vocabulary Emerges from Free-Form Annotations"](https://arxiv.org/abs/1906.01542), Pont-Tuset et al., arXiv 2019.
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6. ["From couloring-in to pointillism: revisiting semantic segmentation supervision"](https://storage.googleapis.com/openimages/web_v7/2022_pointillism_arxiv.pdf), Benenson et al., arXiv 2022.
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