---
title: pixmo-points-eval
canonical_url: "https://www.modelscope.cn/datasets/allenai/pixmo-points-eval"
md_url: "https://www.modelscope.cn/datasets/allenai/pixmo-points-eval.md"
repository: allenai/pixmo-points-eval
last_updated: 2025-05-29
license: "Apache License 2.0"
storage_size: "6.0 MB"
downloads: 604
stars: 0
---

# pixmo-points-eval

> pixmo-points-eval - allenai 在 ModelScope 开源的数据集。PixMo-Points-Eval PixMo-Points-Eval is a subset of PixMo-Points that has been human-filtered and annotated with segmentation masks. It is used for pointing evaluations. PixMo-Points is a part of the PixMo…

allenai/pixmo-points-eval 是 ModelScope 魔搭社区上的数据集，存储大小 6.0 MB，采用 Apache License 2.0 许可。

- **Repository**: allenai/pixmo-points-eval
- **License**: Apache License 2.0
- **Storage size**: 6.0 MB
- **Downloads**: 604
- **Stars**: 0
- **Last updated**: 2025-05-29

Source: https://www.modelscope.cn/datasets/allenai/pixmo-points-eval

---

# PixMo-Points-Eval
PixMo-Points-Eval is a subset of [PixMo-Points](https://huggingface.co/datasets/allenai/pixmo-points) that has been human-filtered and annotated with segmentation masks.
It is used for pointing evaluations.
PixMo-Points is a part of the [PixMo dataset collection](https://huggingface.co/collections/allenai/pixmo-674746ea613028006285687b) and was used to 
provide the pointing capabilities of the [Molmo family of models](https://huggingface.co/collections/allenai/molmo-66f379e6fe3b8ef090a8ca19)

## Loading
```python
data = datasets.load_dataset("allenai/pixmo-points-eval", split="test")
```

## Data Format
Images are stored as URLs that will need to be downloaded separately. Note URLs can be repeated in the data.

The `points` field contains the x, y coordinates specified in pixels.

The `label` field contains the string name of what is being pointed at, this can be a simple object name or a more complex referring expression.

The `masks` field contains the segmentation masks for the points.

## Image Checking
Image hashes are included to support double-checking that the downloaded image matches the annotated image. 
It can be checked like this:

```python
from hashlib import sha256
import requests

example = data[0]
image_bytes = requests.get(example["image_url"]).content
byte_hash = sha256(image_bytes).hexdigest()
assert byte_hash == example["image_sha256"]
```


## License
This dataset is licensed under ODC-BY-1.0. It is intended for research and educational use in accordance with Ai2's [Responsible Use Guidelines](https://allenai.org/responsible-use).