Caption3o-LongCap-v4
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https://modelscope.cn/datasets/prithivMLmods/Caption3o-LongCap-v4
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# **Caption3o-LongCap-v4**
**Caption3o-LongCap-v4** 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
* **Image resolution**: 512x512
* **Languages**: English
* **Modality**: Image-to-Text
* **License**: Apache-2.0
* **Split**: `train` (\~522,825 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-LongCap-v4", split="train")
```
## Citation
If you use this dataset, please cite the original dataset:
And reference this curated derivative:
> **Caption3o-LongCap-v4 by prithivMLmods**

# **Caption3o-LongCap-v4**
**Caption3o-LongCap-v4** 是一款大规模高质量图像-文本标注数据集,专为图像转文本模型的训练与评估打造。该数据集源自 [prithivMLmods/blip3o-caption-mini-arrow](https://huggingface.co/datasets/prithivMLmods/blip3o-caption-mini-arrow) 及其他精选数据源,此优化版本着重支持长文本标注,涵盖了丰富的现实场景与艺术场景。
## 数据集概览
* **图像分辨率**:512×512
* **语言**:英语
* **模态**:图像-文本
* **许可协议**:Apache-2.0
* **数据划分**:训练集(`train`,约522,825条数据)
每张图像均配有详细的描述性标注文本,可支撑视觉语言任务中的长上下文理解与细粒度推理。
## 数据字段
* `image`:512×512分辨率的RGB图像
* `caption`:长格式英文文本(平均长度约500个字符)
示例:
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...
## 应用场景
1. 视觉语言模型的预训练或微调(如BLIP、Flamingo、SigLIP)
2. 长文本图像标注能力的评估
3. 为视觉叙事、场景理解与艺术诠释相关数据集提供增强支持
## 使用方法
可通过Hugging Face的`datasets`库加载该数据集:
python
from datasets import load_dataset
dataset = load_dataset("prithivMLmods/Caption3o-LongCap-v4", split="train")
## 引用说明
若使用本数据集,请引用原始数据集,并标注此衍生整理版本:
> **prithivMLmods 出品的 Caption3o-LongCap-v4 数据集**
提供机构:
maas
创建时间:
2025-09-15



