---
title: Caption3o-Opt-v3
canonical_url: "https://www.modelscope.cn/datasets/prithivMLmods/Caption3o-Opt-v3"
md_url: "https://www.modelscope.cn/datasets/prithivMLmods/Caption3o-Opt-v3.md"
repository: prithivMLmods/Caption3o-Opt-v3
last_updated: 2025-08-29
license: apache-2.0
storage_size: "15 GB"
downloads: 398
stars: 0
---

# Caption3o-Opt-v3

> Caption3o-Opt-v3 - prithivMLmods 在 ModelScope 开源的数据集。Caption3o-Opt-v3 is a large-scale, high-quality image-caption dataset designed for training and evaluating image-to-text models. Derived from prithivMLmods/blip3o-caption-mini-arrow and additional curated…

prithivMLmods/Caption3o-Opt-v3 是 ModelScope 魔搭社区上的数据集，存储大小 15 GB，采用 apache-2.0 许可。

- **Repository**: prithivMLmods/Caption3o-Opt-v3
- **License**: apache-2.0
- **Storage size**: 15 GB
- **Downloads**: 398
- **Stars**: 0
- **Last updated**: 2025-08-29

Source: https://www.modelscope.cn/datasets/prithivMLmods/Caption3o-Opt-v3

---

# **Caption3o-Opt-v3**

**Caption3o-Opt-v3** is a large-scale, high-quality image-caption dataset designed for training and evaluating image-to-text models. Derived from [prithivMLmods/blip3o-caption-mini-arrow](https://huggingface.co/datasets/prithivMLmods/blip3o-caption-mini-arrow) and additional curated sources, this optimized version emphasizes long-form captions and covers a wide range of real-world and artistic scenes.

## Dataset Summary

* **Size**: \~100,000 image-caption pairs (estimated)
* **Format**: Parquet
* **Image resolution**: 512x512
* **Languages**: English
* **Modality**: Image-to-Text
* **License**: Apache-2.0
* **Split**: `train` (\~100k rows)

Each image is paired with a detailed, descriptive caption generated to support long-context understanding and fine-grained reasoning in vision-language tasks.

## Features

* `image`: 512x512 RGB image
* `caption`: Long-form English text (average length \~500 characters)

Example:

```text
The image depicts a serene cemetery with neatly arranged gravestones and headstones, set against a backdrop of lush green grass. The scene is framed by tall trees on either side, their leaves providing dappled shade over the area...
```

## Use Cases

1. Pretraining or finetuning vision-language models (e.g., BLIP, Flamingo, SigLIP)
2. Evaluating long-form image captioning capabilities
3. Enhancing datasets for visual storytelling, scene understanding, and artistic interpretation

## How to Use

You can load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Caption3o-Opt-v3", split="train")
```

## Citation

If you use this dataset, please cite the original dataset:

And reference this curated derivative:

> **Caption3o-Opt-v3 by prithivMLmods**