Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
index: int64
image_path: string
question: string
answer: string
painting_title: null
artist: null
dynasty: null
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 716
to
{'question': Value('string'), 'answer': Value('string'), 'painting_title': Value('string'), 'artist': Value('string'), 'dynasty': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2260, in _iter_arrow
pa_table = cast_table_to_features(pa_table, self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2223, in cast_table_to_features
raise CastError(
datasets.table.CastError: Couldn't cast
index: int64
image_path: string
question: string
answer: string
painting_title: null
artist: null
dynasty: null
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 716
to
{'question': Value('string'), 'answer': Value('string'), 'painting_title': Value('string'), 'artist': Value('string'), 'dynasty': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for ZhiHua_QA
ZhiHua_QA (知画QA) is a specialized dataset focusing on the appreciation, history, and techniques of Chinese Traditional Painting (Guohua). It consists of question-and-answer pairs designed to enhance Large Language Models' (LLMs) understanding of Chinese art aesthetics, historical context, and artistic critique.
Dataset Details
- Curated by: Hangzhou Research Institute of AI and Holographic Technology / Zhejiang University / Hangzhou City University
- Language(s) (NLP): Chinese (Simplified)
- License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Dataset Description
The ZhiHua_QA dataset aims to bridge the gap between general knowledge and the specific domain of Chinese traditional art. While general LLMs are proficient in broad topics, they often lack the nuance required to discuss the "Spirit Resonance" (Qi Yun), brushwork techniques (Gongbi vs. Xieyi), and the historical significance of specific masterpieces.
This dataset contains QA pairs covering various aspects of Chinese painting, including:
- Artistic Analysis: Interpretation of composition, ink usage, and color.
- Historical Context: The background of the artist, the dynasty, and the cultural environment.
- Technique Explanation: Definitions and examples of techniques like "axe-cut strokes" or "boneless" painting.
- Symbolism: The meaning behind common motifs (e.g., plum blossoms, orchids, bamboo, chrysanthemums).
Dataset Sources [optional]
- Repository: [Link to your Hugging Face or GitHub repository]
- Paper [optional]: [Link to a relevant paper if applicable]
- Demo [optional]: [Link to a demo if applicable]
Uses
Direct Use
- Fine-tuning LLMs: To improve the performance of chat models in the domain of art history and Chinese culture.
- Educational Chatbots: Building AI tutors for art students or museum guides.
- Cultural Preservation: Digitizing and structuring knowledge related to intangible cultural heritage.
- Retrieval Augmented Generation (RAG): Serving as a knowledge base for retrieval systems.
Out-of-Scope Use
- Valuation/Appraisal: This dataset is for educational and appreciation purposes only and should not be used to determine the monetary value of real-world artwork.
- Authentication: The data cannot be used to verify the authenticity of physical paintings.
Dataset Structure
The dataset is formatted in tsv lines. Each entry contains the following fields:
index: The index of the items.image_path: The path of the images.question: The user query regarding a specific painting or concept.answer: A detailed, expert-level response explaining the artistic elements.
Example:
index image_path question answer
0 /path/imagedata/墨竹图轴:文同.jpg 这幅画主要描绘了什么内容？ "观察这幅作品，首先映入眼帘的是充满动感的倒垂竹枝造型。画面以单枝竹为主体贯穿全局，展现了中国传统绘画中""孤竹""题材的独特魅力。具体表现如下：
## 核心视觉元素解析
- **主干动态轨迹**：竹枝自左上方斜向垂落，在画面中部形成S形转折后，末端微微上扬至右下方，这种""倒悬而复振""的姿态暗含生命韧劲
- **叶片组织规律**
- **空间分布**：采用""疏可走马，密不透风""的对比手法，近处竹叶密集如云，远处渐次稀疏
- **形态组合**：由多组""个字型""和""介字型""叶片交叠而成，每片叶子都呈现出尖锐挺拔的楔形特征
- **墨色层次**：浓墨勾勒主脉，淡墨渲染叶面，通过墨色深浅暗示叶片的翻转角度
## 构图特征分析
- **对角线张力**：竹枝从左上至右下的延伸轨迹构成强烈的动势，与绢本底纹的静穆感形成微妙平衡
- **留白哲学体现**：画面大面积虚空处理，仅以一枝独秀的方式强化主体，这种极简主义手法凸显文人画""以虚写实""的美学追求
## 文化符号解读
从画面元素可推知，这是一件典型的君子比德之作：
- 竹节象征气节：曲折而不折的枝干隐喻士大夫身处逆境仍保持操守的精神品格
- 叶序寓意同心：叶片虽层层交错却方向一致，暗喻群体精神的凝聚
- 倒生态势象征：反常规生长姿态可能暗示创作者仕途困顿中的自我砥砺
这种单纯以竹为表现对象的构图方式，在宋代文人画中开创了""单枝入画""的新范式，为后世郑板桥等人的竹画创作提供了重要参照。"
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