File size: 2,441 Bytes
40bb8c8 813d5f6 abeda52 ef11150 abeda52 247118f abeda52 f5c6e58 ef11150 f5c6e58 abeda52 40bb8c8 2b5c693 40bb8c8 ca0c77d 40bb8c8 2b5c693 275aa4c 2b5c693 728887f 2b5c693 728887f 2b5c693 275aa4c 40bb8c8 275aa4c 40bb8c8 275aa4c 829027e 813d5f6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
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). |