README.md

---
license: odc-by
dataset_info:
  features:
  - name: image_url
    dtype: string
  - name: image_sha256
    dtype: string
  - name: points
    list:
    - name: x
      dtype: float64
    - name: y
      dtype: float64
  - name: count
    dtype: int64
  - name: label
    dtype: string
  - name: collection_method
    dtype: string
  splits:
  - name: train
    num_bytes: 668565775
    num_examples: 2376222
  download_size: 198336771
  dataset_size: 668565775
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# PixMo-Points
PixMo-Points is a dataset of images paired with referring expressions and points marking the locations the
referring expression refers to in the image. It was collected using human annotators and contains a diverse 
range of points and expressions, with many high-frequency (10+) expressions.

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)

Quick links:
- 📃 [Paper](https://molmo.allenai.org/paper.pdf)
- 🎥 [Blog with Videos](https://molmo.allenai.org/blog)


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

## 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 `collection_method` field specifies whether the image was chosen to target high-frequency counting ("counting") or general pointing ("pointing").

## 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).