Datasets:
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---
dataset_info:
features:
- name: image
dtype: image
- name: segmentation
dtype: image
- name: captions
sequence: string
splits:
- name: train
num_bytes: 1200871225
num_examples: 10000
download_size: 1199201925
dataset_size: 1200871225
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- image-segmentation
- image-to-text
- text-to-image
license: cc-by-4.0
language:
- en
size_categories:
- 1K<n<10K
pretty_name: COCO 2017 segmentation dataset with captions 10k samples
---
## 📄 License and Attribution
This dataset is a downsampled version of the [COCO 2017 dataset](https://cocodataset.org/#home), tailored for segmentation tasks. It has the following fields:
- image: 256x256 image
- segmentation: 256x256 image. Each pixel encodes the class of that pixel. See `class_names_dict.json` for a legend.
- captions: a list of captions for the image, each by a different labeler.
Use the dataset as follows:
```python
import requests
from datasets import load_dataset
ds = load_dataset("peteole/coco2017-segmentation", split="train")
# Optional: Load the class names as dict
url = "https://huggingface.co/datasets/peteole/coco2017-segmentation-10k-256x256/resolve/main/class_names_dict.json"
response = requests.get(url)
class_names_dict = response.json()
```
### License
- **License Type**: [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
- **License Details**: This license permits redistribution, modification, and commercial use, provided that appropriate credit is given to the original creators.
- **Original Dataset License**: The original COCO 2017 dataset is licensed under CC BY 4.0.
### Attribution
When using this dataset, please cite the original COCO dataset as follows:
> 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.
For more information, visit the [COCO dataset website](https://cocodataset.org/#home). |