File size: 1,458 Bytes
b99068b e062197 5a366da e062197 |
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 |
---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 83803600.0
num_examples: 100000
- name: validation
num_bytes: 8609095.48
num_examples: 10240
- name: test
num_bytes: 17218416.240000002
num_examples: 20480
download_size: 74270288
dataset_size: 109631111.72
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
## Arrow Pointing Extrapolation
This dataset contains the exact images used for the extrapolation experiments in [pLSTM](https://huggingface.co/papers/2506.11997).
It is a synthetic dataset of arrows pointing to circles and should measure how well an image model can learn the classification
'if the arrow points to the circle' at small (192x192) scales and extrapolate/generalize (without previous resizing of the image input)
to larger scales (384x384).
Note that for the correct validation and test extrapolation subsets, you have to filter for the larger images:
```
from datasets import load_dataset
ds = load_dataset('ml-jku/arrow_pointing_extrapolation')
ds_val_ext = ds['validation'].filter(lambda sample: sample['image'].size == (384, 384))
ds_test_ext = ds['test'].filter(lambda sample: sample['image'].size == (384, 384))
```
|