| --- |
| pretty_name: Mixed Parts |
| language: |
| - en |
| task_categories: |
| - image-segmentation |
| tags: |
| - computer-vision |
| - semantic-segmentation |
| - co-segmentation |
| - part-segmentation |
| - multi-image-reasoning |
| size_categories: |
| - 1M<n<10M |
| --- |
| |
| # Mixed Parts |
|
|
| Mixed Parts is the annotation bundle used by CALICO for part-focused semantic co-segmentation. It contains multi-image object-part comparison samples curated from ADE20KPart234, PartImageNet, and PACO-LVIS image assets. |
|
|
| This repository contains annotations only. Users must download the original image datasets separately from their upstream sources and overlay these annotations into the expected CALICO directory structure. |
|
|
| ## Files |
|
|
| ```text |
| mixed_parts_train.json |
| mixed_parts_val.json |
| mixed_parts_test.json |
| ADE20KPart234/ade20k_instance_train_mixed_parts.json |
| ADE20KPart234/ade20k_instance_val_mixed_parts.json |
| PartImageNet/annotations/train/train_mixed_parts.json |
| PartImageNet/annotations/train_whole/train_mixed_parts.json |
| PartImageNet/annotations/val/val_mixed_parts.json |
| PartImageNet/annotations/val_whole/val_mixed_parts.json |
| PartImageNet/annotations/test/test_mixed_parts.json |
| PartImageNet/annotations/test_whole/test_mixed_parts.json |
| ``` |
|
|
| The official Mixed Parts test split is `mixed_parts_test.json`. |
|
|
| ## Split Sizes |
|
|
| | Split | Samples | |
| | --- | ---: | |
| | Train | 2,380,749 | |
| | Val | 1,999 | |
| | Test | 999 | |
|
|
| ## Source Data |
|
|
| Download the original source data from the upstream projects: |
|
|
| - ADE20KPart234: download `ADE20KPart234.tar.gz` from [InternRobotics/OV_PARTS](https://github.com/InternRobotics/OV_PARTS). |
| - PartImageNet: download `PartImageNet_Seg.zip` from [tacju/partimagenet](https://github.com/tacju/partimagenet). |
| - COCO2017 and PACO-LVIS: follow [facebookresearch/paco](https://github.com/facebookresearch/paco) and download `paco_lvis_v1.zip`. PACO-LVIS annotations reference COCO2017 images, so COCO2017 images are also required. |
|
|
| ## Data Preparation |
|
|
| From the CALICO repository root, create the default data layout: |
|
|
| ```bash |
| mkdir -p data/mixed_parts_data data/coco_2017 |
| ``` |
|
|
| Extract ADE20KPart234 and PartImageNet under `data/mixed_parts_data`: |
|
|
| ```bash |
| tar -xzf /path/to/ADE20KPart234.tar.gz -C data/mixed_parts_data |
| unzip /path/to/PartImageNet_Seg.zip -d data/mixed_parts_data |
| ``` |
|
|
| Extract PACO-LVIS annotations under `data/mixed_parts_data/paco_lvis/annotations`: |
|
|
| ```bash |
| mkdir -p data/mixed_parts_data/paco_lvis/annotations |
| unzip /path/to/paco_lvis_v1.zip -d data/mixed_parts_data/paco_lvis/annotations |
| ``` |
|
|
| Place COCO2017 images under `data/coco_2017`: |
|
|
| ```text |
| data/coco_2017/ |
| ├── train2017/ |
| └── val2017/ |
| ``` |
|
|
| Download this annotation bundle directly into `data/mixed_parts_data`: |
|
|
| ```bash |
| huggingface-cli download PLAN-Lab/MixedParts \ |
| --repo-type dataset \ |
| --local-dir data/mixed_parts_data \ |
| --local-dir-use-symlinks False |
| ``` |
|
|
| If you downloaded the bundle somewhere else, overlay it into `data/mixed_parts_data`: |
|
|
| ```bash |
| cp -r /path/to/MixedParts/* data/mixed_parts_data/ |
| ``` |
|
|
| The prepared data should have this structure: |
|
|
| ```text |
| data/ |
| ├── coco_2017/ |
| │ ├── train2017/ |
| │ └── val2017/ |
| └── mixed_parts_data/ |
| ├── mixed_parts_train.json |
| ├── mixed_parts_val.json |
| ├── mixed_parts_test.json |
| ├── ADE20KPart234/ |
| │ ├── ade20k_instance_train_mixed_parts.json |
| │ ├── ade20k_instance_val_mixed_parts.json |
| │ ├── images/ |
| │ └── annotations_detectron2_part/ |
| ├── PartImageNet/ |
| │ ├── annotations/ |
| │ │ ├── train/train_mixed_parts.json |
| │ │ ├── train_whole/train_mixed_parts.json |
| │ │ ├── val/val_mixed_parts.json |
| │ │ ├── val_whole/val_mixed_parts.json |
| │ │ ├── test/test_mixed_parts.json |
| │ │ └── test_whole/test_mixed_parts.json |
| │ └── images/ |
| └── paco_lvis/ |
| └── annotations/ |
| ├── paco_lvis_v1_train.json |
| ├── paco_lvis_v1_val.json |
| └── paco_lvis_v1_test.json |
| ``` |
|
|
| ## Evaluation with CALICO |
|
|
| After preparing the data, run evaluation from the CALICO repository root: |
|
|
| ```bash |
| python evaluate.py \ |
| --merged_ckpt_path PLAN-Lab/CALICO \ |
| --dataset_dir ./data \ |
| --output_save_path ./evaluate_results/calico_mixed_parts \ |
| --val_dataset "MixedPartsObjectVal|MixedPartsPartVal" \ |
| --multi_image_filepath_prefix ./data/mixed_parts_data/mixed_parts_test.json \ |
| --mode test \ |
| --compute_metrics |
| ``` |
|
|
| For full setup details, see the CALICO repository documentation. |
|
|
| ## Licensing and Terms |
|
|
| This repository provides Mixed Parts annotations for research use. The underlying images and source annotations come from ADE20KPart234, PartImageNet, COCO2017, and PACO-LVIS. Users are responsible for following the licenses and terms of the upstream datasets. |
|
|
| ## Citation |
|
|
| If you use Mixed Parts or CALICO, please cite: |
|
|
| ```bibtex |
| @article{nguyen2025calico, |
| title={CALICO: Part-Focused Semantic Co-Segmentation with Large Vision-Language Models}, |
| author={Nguyen, Kiet A. and Juvekar, Adheesh and Yu, Tianjiao and Wahed, Muntasir and Lourentzou, Ismini}, |
| journal={In Proceedings for the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
| year={2025} |
| } |
| ``` |
|
|