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--- |
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license: cc |
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dataset_info: |
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features: |
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- name: mask |
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dtype: image |
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- name: segments_info |
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struct: |
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- name: file_name |
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dtype: string |
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- name: image_id |
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dtype: int64 |
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- name: segments_info |
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list: |
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- name: area |
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dtype: int64 |
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- name: category_id |
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dtype: int64 |
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- name: id |
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dtype: int64 |
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- name: iscrowd |
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dtype: int64 |
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- name: isthing |
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dtype: int64 |
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- name: image_info |
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struct: |
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- name: coco_url |
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dtype: string |
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- name: date_captured |
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dtype: string |
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- name: file_name |
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dtype: string |
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- name: height |
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dtype: int64 |
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- name: id |
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dtype: int64 |
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- name: license |
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dtype: int64 |
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- name: width |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 35063720.0 |
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num_examples: 5000 |
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download_size: 32911960 |
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dataset_size: 35063720.0 |
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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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--- |
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## How to download |
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1. Set up environment |
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``` |
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pip install datasets tqdm |
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wget https://raw.githubusercontent.com/bytedance/coconut_cvpr2024/main/download_coconut.py |
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``` |
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2. Use the download script to download the COCONut dataset splits. |
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``` |
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python download_coconut.py # default split: relabeled_coco_val |
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``` |
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The above command should print your download status, if you download it successfully you can see the results below: |
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 |
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3. Download other COCONut dataset splits. |
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If you want to download the other splits, you can replace the split name to "coconut_s" or "coconut_b" |
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NOTE: multiple splits download is not yet supported. |
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``` |
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python download_coconut.py --split coconut_s --output_dir coconut_s |
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``` |
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4. The mask images are nearly black as we use continuous segment ids for each image, you can use our [github visualization tutorial](https://github.com/bytedance/coconut_cvpr2024/blob/main/tutorials/visualization/demo.ipynb) to create colorful masks for viewing. |
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Please go to our offical github repo for detailed usage instruction: https://github.com/bytedance/coconut_cvpr2024 |
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