---
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}
}
```