--- task_categories: - object-detection dataset_info: features: - name: image_id dtype: string - name: image dtype: image - name: label_bbox list: - name: bbox sequence: int64 - name: bbox_id dtype: string - name: label dtype: string - name: issues list: - name: confidence dtype: float64 - name: description dtype: string - name: issue_type dtype: string splits: - name: train num_bytes: 13436697177.0 num_examples: 82081 - name: validation num_bytes: 6606403140.0 num_examples: 40137 - name: test num_bytes: 6653024122.0 num_examples: 40775 download_size: 26617129269 dataset_size: 26696124439.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* --- [![Visualize Dataset on Visual Layer](https://img.shields.io/badge/Visualize%20on-%20Visual%20Layer-purple?style=for-the-badge&logo=numpy)](https://app.visual-layer.com/dataset/acd886ce-2b9f-11ef-bb10-e605d78f584b/data?p=1&page=1) # COCO-2014-VL-Enriched An enriched version of the COCO 2014 dataset with label issues! The label issues helps 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.: ```python import datasets ds = datasets.load_dataset("visual-layer/coco-2014-vl-enriched") ``` More in this [notebook](usage.ipynb). ## 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](https://app.visual-layer.com/dataset/acd886ce-2b9f-11ef-bb10-e605d78f584b/data?p=1&page=1). 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 ImageNet-1K dataset license. ## About Visual Layer