allenai/pixmo-points
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 and was used to provide the pointing capabilities of the Molmo family of models Quick links: π Paper π₯ Blog withβ¦ See the full description on the dataset page: https://huggingface.co/datasets/allenai/pixmo-points.
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 and was used to provide the pointing capabilities of the Molmo family of models
Quick links:
- π Paper
- π₯ Blog with Videos
Loading
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:
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.
