size_categories:1K<n<10K format:parquet modality:image modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
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  - name: dataset_name
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  - name: org_id
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  - name: target
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  splits:
  - name: train
    num_bytes: 288167
    num_examples: 1350
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configs:
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    path: data/train-*
---

# Dataset Description

This dataset includes 1350 images of objects of varied counts, 150 images for each count between 2 and 10. It consists of images automatically sourced from multiple sources, including the COCO Dataset, Conceptual 12M, YFCC100M, and SBU Captions Dataset. In addition, due to the fact that images with large counts (i.e., nine and ten) are scarce, to compose 150 images for each count, we also manually collect some images from the Internet. Each text image pair is manually checked and the captions are revised to get rid of grammar errors and noisy information. Images are also manually checked to avoid duplication. This dataset can be used to train to improve or evaluate a visual language model's object counting accuracy.
