| dataset_info: | |
| features: | |
| - name: images | |
| sequence: image | |
| - name: problem | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 106400000 | |
| num_examples: 500 | |
| download_size: 106400000 | |
| dataset_size: 106400000 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| # Stepcount-500 | |
| ## Dataset Description | |
| Stepcount-500 is a benchmark dataset of 500 counting samples with object counts ranging from 11 to 50. | |
| ## Dataset Structure | |
| ### Data Fields | |
| - `images`: A sequence of images (one image per sample) | |
| - `problem`: The question text describing the counting task | |
| - `answer`: The ground truth count number | |
| ### Data Splits | |
| - **train**: 500 evaluation samples | |
| ## Dataset Statistics | |
| - Count range: 11-50 | |
| - Distribution: 11-20 (130), 21-30 (130), 31-40 (120), 41-50 (120) | |
| - Total dataset size: approximately 106 MB | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("SI-Lab/Stepcount-500") | |
| ``` | |