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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: segmentation |
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dtype: image |
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- name: captions |
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sequence: string |
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splits: |
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- name: train |
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num_bytes: 1200871225 |
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num_examples: 10000 |
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download_size: 1199201925 |
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dataset_size: 1200871225 |
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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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task_categories: |
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- image-segmentation |
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- image-to-text |
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- text-to-image |
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license: cc-by-4.0 |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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pretty_name: COCO 2017 segmentation dataset with captions 10k samples |
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--- |
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## 📄 License and Attribution |
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This dataset is a downsampled version of the [COCO 2017 dataset](https://cocodataset.org/#home), tailored for segmentation tasks. It has the following fields: |
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- image: 256x256 image |
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- segmentation: 256x256 image. Each pixel encodes the class of that pixel. See `class_names_dict.json` for a legend. |
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- captions: a list of captions for the image, each by a different labeler. |
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Use the dataset as follows: |
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```python |
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import requests |
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from datasets import load_dataset |
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ds = load_dataset("peteole/coco2017-segmentation", split="train") |
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# Optional: Load the class names as dict |
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url = "https://huggingface.co/datasets/peteole/coco2017-segmentation-10k-256x256/resolve/main/class_names_dict.json" |
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response = requests.get(url) |
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class_names_dict = response.json() |
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``` |
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### License |
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- **License Type**: [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) |
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- **License Details**: This license permits redistribution, modification, and commercial use, provided that appropriate credit is given to the original creators. |
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- **Original Dataset License**: The original COCO 2017 dataset is licensed under CC BY 4.0. |
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### Attribution |
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When using this dataset, please cite the original COCO dataset as follows: |
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> Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár. "Microsoft COCO: Common Objects in Context." In *European Conference on Computer Vision*, pp. 740–755. Springer, 2014. |
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For more information, visit the [COCO dataset website](https://cocodataset.org/#home). |
