Duplicate from songjhPKU/U-RxnDiagram-15k

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+*.pcm filter=lfs diff=lfs merge=lfs -text
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README.md

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+# U-RxnDiagram-15k Dataset
+
+## Dataset Overview
+
+U-RxnDiagram-15k Dataset is a large-scale dataset specifically designed for chemical reaction diagram parsing, containing chemical reaction images extracted from scientific literature PDFs along with detailed annotations. This dataset aims to support research in cheminformatics, document analysis, and computer vision fields.
+
+## Dataset Statistics
+
+- **Total Images**: 15,400 images
+  - Train set: 15,000 images
+  - Test set: 400 images
+- **Total Reactions**: 48,255 reactions
+  - Train set: 45,426 reactions
+  - Test set: 2,829 reactions
+- **Data Source**: Scientific literature PDF files
+- **Image Format**: PNG
+- **Total Annotations**: Approximately 165,468 annotation instances
+
+## Dataset Structure
+
+```
+U-RxnDiagram-15k/
+├── train_set/
+│   ├── ground_truth.json          # Train set annotation file
+│   └── images/                    # Train set image directory
+└── test_set/
+    ├── ground_truth.json          # Test set annotation file
+    └── images/                    # Test set image directory
+```
+
+## Annotation Category Definitions
+
+The dataset defines 4 main categories, each containing multiple fine-grained attributes:
+
+### 1. Structure - category_id: 1
+- **P-reactant**: Reactant molecular structures
+- **P-product**: Product molecular structures
+- **P-reaction condition**: Reaction condition molecular structures
+
+### 2. Text - category_id: 2
+- **T-reaction condition**: Reaction condition text
+- **T-reactant**: Reactant text
+- **T-product**: Product text
+
+### 3. Identifier - category_id: 3
+- Chemical identifiers and numbers
+
+### 4. Supplement - category_id: 4
+- Other supplementary information
+
+## Annotation Statistics
+
+### Train Set
+| Attribute Type | Annotation Count | Percentage |
+|---------------|------------------|------------|
+| T-reaction condition | 56,377 | 35.84% |
+| P-reactant | 31,779 | 20.20% |
+| P-product | 30,808 | 28.79% |
+| T-reactant | 6,433 | 6.02% |
+| T-product | 3,804 | 2.42% |
+| P-reaction condition | 6,230 | 3.96% |
+
+### Test Set
+| Attribute Type | Annotation Count | Percentage |
+|---------------|------------------|------------|
+| T-reaction condition | 3,011 | 36.92% |
+| P-reactant | 1,521 | 18.65% |
+| P-product | 2,348 | 28.79% |
+| T-reactant | 491 | 6.02% |
+| T-product | 388 | 4.76% |
+| P-reaction condition | 397 | 4.87% |
+
+## Data Format
+
+### Image File Naming
+Image filenames are hashed (SHA-256, first 8 hex chars).
+Example: `a1b2c3d4.png`.
+
+
+### Annotation File Format (ground_truth.json)
+
+The annotation file follows COCO format and contains the following main fields:
+
+```json
+{
+  "licenses": [...],
+  "info": {
+    "description": "A dataset for chemical visual diagram analysis",
+    "version": "v1",
+    "year": "2025"
+  },
+  "categories": [
+    {"id": 1, "name": "structure"},
+    {"id": 2, "name": "text"},
+    {"id": 3, "name": "identifier"},
+    {"id": 4, "name": "supplement"}
+  ],
+  "images": [
+    {
+      "id": 2,
+      "class": "figure",
+      "confidence": 0.9148465991020203,
+      "bbox": [x1, y1, x2, y2],
+      "original_id": 0,
+      "width": 1008.7104797363281,
+      "height": 471.88232421875,
+      "file_name": "ays765k9.png",
+      "bboxes": [
+        {
+          "id": 0,
+          "bbox": [x, y, width, height],
+          "category_id": 1,
+          "category": "P",
+          "attribute": "P-reactants",
+          "region_id": ["akzkPsql"]
+        }
+      ]
+    }
+  ]
+}
+```
+
+### Annotation Field Descriptions
+
+- **id**: Unique annotation identifier
+- **bbox**: Bounding box coordinates [x1, y1, x2, y2] for image-level bbox, [x, y, width, height] for bboxes list
+- **category_id**: Category ID (1-4)
+- **category**: Category abbreviation (P=Structure, T=Text)
+- **attribute**: Specific attribute name
+- **region_id**: List of region identifiers
+
+## Use Cases
+
+This dataset is suitable for the following research tasks:
+
+1. **Chemical Structure Recognition**: Identify and locate molecular structures in chemical reactions
+2. **Text Information Extraction**: Extract text information from chemical diagrams
+3. **Reaction Condition Analysis**: Identify and analyze reaction conditions
+4. **Document Understanding**: Understand chemical information in scientific literature
+5. **Multimodal Learning**: Combine visual and text information for chemical analysis
+
+## Data Quality
+
+- All images are sourced from high-quality scientific literature
+- Annotations are professionally verified for accuracy
+- Contains samples of various chemical reaction types and complexities
+- Supports fine-grained chemical information analysis
+
+<!-- ## Citation
+
+If you use this dataset in your research, please cite the relevant paper:
+
+```bibtex
+@dataset{rxncaption15k_2025,
+  title={U-RxnDiagram-15k: A Dataset for Chemical Reaction Diagram Parsing},
+  author={[Authors]},
+  year={2025},
+  version={v1},
+  description={A large-scale dataset for chemical reaction visual analysis extracted from scientific literature PDFs}
+}
+``` -->
+
+## License
+
+This dataset is licensed under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/).
+
+### Terms of Use
+
+You are free to:
+- **Share** — copy and redistribute the material in any medium or format
+- **Adapt** — remix, transform, and build upon the material
+
+Under the following terms:
+- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
+- **NonCommercial** — You may not use the material for commercial purposes. Commercial use is prohibited without explicit permission from the licensor.
+
+### Citation
+
+If you use this dataset in your research, please cite it as follows:
+
+```bibtex
+@article{song2025rxncaption,
+  title={RxnCaption: Reformulating Reaction Diagram Parsing as Visual Prompt Guided Captioning},
+  author={Song, Jiahe and Wang, Chuang and Jiang, Bowen and Wang, Yinfan and Zheng, Hao and Wei, Xingjian and Liu, Chengjin and Nie, Rui and Gao, Junyuan and Sun, Jiaxing and others},
+  journal={arXiv preprint arXiv:2511.02384},
+  year={2025}
+}
+```
+
+## Contact
+
+For questions or suggestions, please contact songjiahe@pjlab.org.cn
+
+---
+
+*Last updated: 2025*

README_ZH.md

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+# U-RxnDiagram-15k 数据集
+
+## 数据集概述
+
+U-RxnDiagram-15k 数据集是一个专门用于化学反应图表解析的大规模数据集，包含从科学文献PDF中提取的化学反应图像及其详细标注。该数据集旨在支持化学信息学、文档分析和计算机视觉领域的研究。
+
+## 数据集统计信息
+
+- **总图像数量**: 15,400 张
+  - 训练集: 15,000 张图像
+  - 测试集: 400 张图像
+- **总反应数量**: 48,255 个反应
+  - 训练集: 45,426 个反应
+  - 测试集: 2,829 个反应
+- **数据来源**: 科学文献PDF文件
+- **图像格式**: PNG
+- **标注总数**: 约 165,468 个标注实例
+
+## 数据集结构
+
+```
+U-RxnDiagram-15k/
+├── train_set/
+│   ├── ground_truth.json          # 训练集标注文件
+│   └── images/                    # 训练集图像目录
+└── test_set/
+    ├── ground_truth.json          # 测试集标注文件
+    └── images/                    # 测试集图像目录
+```
+
+## 标注类别定义
+
+数据集定义了4个主要类别，每个类别包含多个细分的属性：
+
+### 1. Structure (分子结构) - category_id: 1
+- **P-reactants**: 反应物分子
+- **P-product**: 产物分子
+- **P-reaction conditions**: 反应条件
+
+### 2. Text (文本) - category_id: 2
+- **T-reaction conditions**: 反应条件文本
+- **T-reactants**: 反应物文本
+- **T-product**: 产物文本
+
+### 3. Identifier (标识符) - category_id: 3
+- 化学标识符和编号
+
+### 4. Supplement (补充信息) - category_id: 4
+- 其他补充信息
+
+## 标注统计
+
+### 训练集
+| 属性类型 | 标注数量 | 占比 |
+|---------|---------|------|
+| T-reaction condition | 56,377 | 35.84% |
+| P-reactant | 31,779 | 20.20% |
+| P-product | 30,808 | 28.79% |
+| T-reactant | 6,433 | 6.02% |
+| T-product | 3,804 | 2.42% |
+| P-reaction condition | 6,230 | 3.96% |
+
+### 测试集
+| 属性类型 | 标注数量 | 占比 |
+|---------|---------|------|
+| T-reaction condition | 3,011 | 36.92% |
+| P-reactant | 1,521 | 18.65% |
+| P-product | 2,348 | 28.79% |
+| T-reactant | 491 | 6.02% |
+| T-product | 388 | 4.76% |
+| P-reaction condition | 397 | 4.87% |
+
+## 数据格式
+
+### 图像文件命名
+图像文件名已进行哈希处理（SHA-256 前 8 位）。
+例如：`a1b2c3d4.png`。
+
+### 标注文件格式 (ground_truth.json)
+
+标注文件采用COCO格式，包含以下主要字段：
+
+```json
+{
+  "licenses": [...],
+  "info": {
+    "description": "A dataset for chemical visual diagram analysis",
+    "version": "v1",
+    "year": "2025"
+  },
+  "categories": [
+    {"id": 1, "name": "structure"},
+    {"id": 2, "name": "text"},
+    {"id": 3, "name": "identifier"},
+    {"id": 4, "name": "supplement"}
+  ],
+  "images": [
+    {
+      "id": 2,
+      "class": "figure",
+      "confidence": 0.9148465991020203,
+      "bbox": [x1, y1, x2, y2],
+      "original_id": 0,
+      "width": 1008.7104797363281,
+      "height": 471.88232421875,
+      "file_name": "ays765k9.png",
+      "bboxes": [
+        {
+          "id": 0,
+          "bbox": [x, y, width, height],
+          "category_id": 1,
+          "category": "P",
+          "attribute": "P-reactants",
+          "region_id": ["akzkPsql"]
+        }
+      ]
+    }
+  ]
+}
+```
+
+### 标注字段说明
+
+- **id**: 标注唯一标识符
+- **bbox**: 边界框坐标 [x1, y1, x2, y2] 用于图像级bbox，[x, y, width, height] 用于bboxes列表
+- **category_id**: 类别ID (1-4)
+- **category**: 类别简称 (P=结构, T=文本)
+- **attribute**: 具体属性名称
+- **region_id**: 区域标识符列表
+
+## 使用场景
+
+该数据集适用于以下研究任务：
+
+1. **化学结构识别**: 识别和定位化学反应中的分子结构
+2. **文本信息提取**: 从化学图表中提取文本信息
+3. **反应条件分析**: 识别和分析反应条件
+4. **文档理解**: 理解科学文献中的化学信息
+5. **多模态学习**: 结合视觉和文本信息进行化学分析
+
+## 数据质量
+
+- 所有图像均来自高质量的科学文献
+- 标注经过专业验证，确保准确性
+- 包含多种化学反应类型和复杂度的样本
+- 支持细粒度的化学信息分析
+
+## 引用
+
+如果您在研究中使用了此数据集，请引用相关论文：
+
+```bibtex
+@article{song2025rxncaption,
+  title={RxnCaption: Reformulating Reaction Diagram Parsing as Visual Prompt Guided Captioning},
+  author={Song, Jiahe and Wang, Chuang and Jiang, Bowen and Wang, Yinfan and Zheng, Hao and Wei, Xingjian and Liu, Chengjin and Nie, Rui and Gao, Junyuan and Sun, Jiaxing and others},
+  journal={arXiv preprint arXiv:2511.02384},
+  year={2025}
+}
+```
+
+## 许可证
+
+本数据集采用 [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/) 许可证。
+
+### 使用条款
+
+您可以自由地：
+- **共享** — 以任何媒介或格式复制和重新分发材料
+- **改编** — 对材料进行混��、转换和构建
+
+在以下条件下：
+- **署名** — 您必须给出适当的署名，提供指向本许可协议的链接，同时标明是否对原始作品作了修改。您可以用任何合理的方式来署名，但是不得以任何方式暗示许可方认可您或您的使用。
+- **非商业性使用** — 您不得将本材料用于商业目的。未经许可方明确许可，禁止商业使用。
+
+### 引用格式
+
+如果您在研究中使用了本数据集，请按以下格式引用：
+
+<!-- ```bibtex
+@dataset{rxncaption11k_2025,
+  title={RxnCaption-11k: A Dataset for Chemical Reaction Diagram Parsing},
+  author={[Authors]},
+  year={2025},
+  version={v1},
+  license={CC BY 4.0},
+  url={[Dataset URL]},
+  description={A large-scale dataset for chemical reaction visual analysis extracted from scientific literature PDFs}
+} -->
+```
+
+## 联系方式
+
+如有问题或建议，请联系 songjiahe@pjlab.org.cn
+
+---
+
+*最后更新: 2025年*

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