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---
license: cc
dataset_info:
features:
- name: mask
dtype: image
- name: segments_info
struct:
- name: file_name
dtype: string
- name: image_id
dtype: int64
- name: segments_info
list:
- name: category_id
dtype: int64
- name: id
dtype: int64
- name: iscrowd
dtype: int64
- name: isthing
dtype: int64
- name: image_info
struct:
- name: coco_url
dtype: string
- name: date_captured
dtype: string
- name: file_name
dtype: string
- name: height
dtype: int64
- name: id
dtype: int64
- name: license
dtype: int64
- name: width
dtype: int64
splits:
- name: train
num_bytes: 874203347.2
num_examples: 118200
download_size: 817249090
dataset_size: 874203347.2
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
## How to download
1. Set up environment
```
pip install datasets tqdm
wget https://raw.githubusercontent.com/bytedance/coconut_cvpr2024/main/download_coconut.py
```
2. Use the download script to download the COCONut dataset splits.
```
python download_coconut.py --split coconut_s # default split: relabeled_coco_val, need to switch to coconut_s
```
The above command should print your download status, if you download it successfully you can see the results below:
3. Download other COCONut dataset splits.
If you want to download the other splits, you can replace the split name to "relabeled_coco_val" or "coconut_b"
NOTE: multiple splits download is not yet supported.
```
python download_coconut.py --split relabeled_coco_val --output_dir relabeled_coco_val
```
4. The mask images are nearly black as we use continuous segment ids for each image, you can use [github visualization tutorial](https://github.com/bytedance/coconut_cvpr2024/blob/main/tutorials/visualization/demo.ipynb) to create colorful masks for viewing.
Please go to our offical github repo for detailed usage instruction: https://github.com/bytedance/coconut_cvpr2024
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