---
pretty_name: CaptionExam
license: other
license_name: research-only
license_link: LICENSE
language:
- en
task_categories:
- image-to-text
- visual-question-answering
tags:
- image-captioning
- dense-captioning
- benchmark
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: test
    path: images/**
---

# CaptionExam

109 images and 3,099 fine-grained multiple-choice questions about them, for grading image captions: a text-only judge answers each question from a caption alone. Every question includes the option *"not mentioned / indeterminable"*, which is never the answer. Evaluation code: [Ki-Seki/CaptionExam](https://github.com/Ki-Seki/CaptionExam).

The images are photos, illustrations, product shots, posters, book covers and text-heavy graphics. Each has 15–42 questions (median 27) about objects and counts, colors and materials, pose and orientation, layout, rendered text and its exact wording, typography, style and background.

## Format

`questions.jsonl` has one question per line, and `images/metadata.jsonl` repeats each image's questions alongside the image.

```json
{"id": "img_0001_q02", "image_id": "img_0001",
 "question": "What color is the body of the pickup truck parked under the carport?",
 "options": ["white or light silver", "dark blue or black", "red or maroon", "dark green",
             "not mentioned / indeterminable"],
 "answer": ["white or light silver"],
 "bbox": [453, 552, 622, 804]}
```

`bbox` is the region the question is about, as `[y_min, x_min, y_max, x_max]` normalized to 0–1000. 120 questions cover the whole image.

```python
from datasets import load_dataset

ds = load_dataset("Ki-Seki/CaptionExam", split="test")  # one row per image, with its questions
```

## License

The questions and annotations are for research use. The images were collected from the public web and their copyright stays with their owners; they are provided only for non-commercial research and evaluation. To have an image removed, open an issue at [Ki-Seki/CaptionExam](https://github.com/Ki-Seki/CaptionExam/issues).