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000000057870
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000000069675
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000000547471
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000000122688
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000000392136
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000000398494
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000000090570
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000000161919
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000000044404
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000000004428
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null
000000280980
[ { "bbox": [ 287, 197, 122, 130 ], "bbox_id": "f2e0377d-7d16-485f-a777-0b1ba5babdc8", "label": "toilet" }, { "bbox": [ 208, 139, 19, 32 ], "bbox_id": "d6aa0e5c-c7cf-44ae-8792-48110d9c1aae", "label": "cup" }, { "bbox": [ 103, 8, 122, 321 ], "bbox_id": "fa68adc6-210b-4d82-93b2-ce1f3033c6e8", "label": "person" }, { "bbox": [ 448, 153, 51, 105 ], "bbox_id": "ab0eeb1a-0530-41d8-aa92-e7021c0598a4", "label": "backpack" }, { "bbox": [ 99, 63, 83, 132 ], "bbox_id": "f3f02c9f-a0c7-44cc-a82f-bc916e8b8b48", "label": "handbag" } ]
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[ { "bbox": [ 448, 71, 168, 105 ], "bbox_id": "8504c759-b89c-4fd8-bf71-e4fcf5c15cb1", "label": "sink" }, { "bbox": [ 236, 198, 124, 176 ], "bbox_id": "8fc301ff-b000-43fd-b225-70e4473bea8b", "label": "toilet" } ]
null
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[ { "bbox": [ 230, 209, 225, 203 ], "bbox_id": "0500705e-9851-46ba-b56c-e4c77f7847dd", "label": "motorcycle" }, { "bbox": [ 466, 178, 16, 28 ], "bbox_id": "033e49e6-557f-42e1-9868-01e9aa388214", "label": "clock" } ]
null
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[ { "bbox": [ 190, 158, 201, 429 ], "bbox_id": "40fae1e5-afaa-466f-8401-f4d9aa218831", "label": "toilet" } ]
null
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[ { "bbox": [ 41, 312, 198, 99 ], "bbox_id": "b257c125-dd0d-41d7-936d-f66a49a02e15", "label": "sink" }, { "bbox": [ 282, 254, 107, 51 ], "bbox_id": "ef09c808-f0e6-45f4-9099-e69a92c868a8", "label": "sink" }, { "bbox": [ 247, 335, 175, 251 ], "bbox_id": "7f4b9105-addb-4a39-8ff4-210a8bcdf805", "label": "toilet" } ]
null
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COCO-2014-VL-Enriched

An enriched version of the COCO 2014 dataset with label issues! The label issues help to curate a cleaner and leaner dataset.

Description

The dataset consists of 6 columns:

  • image_id: The original image filename from the COCO dataset.
  • image: Image data in the form of PIL Image.
  • label_bbox: Bounding box annotations from the COCO dataset. Consists of bounding box coordinates, confidence scores, and labels for the bounding box generated using object detection models.
  • issues: Quality issues found such as duplicate, mislabeled, dark, blurry, bright, and outlier images.

Usage

This dataset can be used with the Hugging Face Datasets library.:

import datasets
ds = datasets.load_dataset("visual-layer/coco-2014-vl-enriched")

More in this notebook.

Interactive Visualization

Visual Layer provides a platform to interactively visualize a dataset and highlight quality issues such as duplicates, mislabels, outliers, etc. Check it out here. No sign-up required.

License & Disclaimer

We provide no warranty on the dataset, and the user takes full responsibility for the usage of the dataset. By using the dataset, you agree to the terms of the COCO dataset license.

About Visual Layer

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