https://github.com/scut-dlvclab/megahan97k

MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories
https://github.com/scut-dlvclab/megahan97k

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MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories

• Host: GitHub
• URL: https://github.com/scut-dlvclab/megahan97k
• Owner: SCUT-DLVCLab
• Created: 2024-05-27T11:40:20.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-07-19T08:26:07.000Z (10 months ago)
• Last Synced: 2024-07-19T16:54:39.887Z (10 months ago)
• Language: Python
• Homepage:
• Size: 38.3 MB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
MegaHan97K Dataset




 MegaHan97K: A Large-Scale Dataset for Mega-Category Chinese Character Recognition with over 97K Categories 

Pattern Recognition (PR), 2025



* We introduce MegaHan97K, a mega-category, large-scale dataset that contains the largest 97,455 Chinese character categories.

* MegaHan97K includes Chinese characters of 97,455 categories, which significantly surpasses existing datasets with at least six times larger categories and holds the largest volume.

* MegaHan97K pioneers to support the latest Chinese GB18030-2022 standard, ensuring the most comprehensive coverage and compatibility with modern Chinese processing systems.

* MegaHan97K contains three distinct subsets: handwritten, historical, and synthetic. Each subset contains a greater number of character categories compared to existing datasets, resulting in remarkable scale and diversity advantages.

* MegaHan97K effectively mitigates long-tail distribution issues by providing a balanced and sufficient number of samples for each category, ensuring robust training and validation of CCR models.

![overview](/images/overview.png)

## 🔥 Download

| **Setting**             | **Dataset** | **status** |

|-------------------------|----------------|------------|

| **General CCR**         | [Baiduyun:k4ch](https://pan.baidu.com/s/1LwIS-K812Q0LjBajpvQeVw?pwd=k4ch)/[OneDrive](https://1drv.ms/u/c/d3b0ec8fe3491f94/EYi4e5_dtLBMmFl9I669KjEBr2PqPWEd7VLxeIzHDlKhgg?e=YXrQEO) | Released |

| **Zero-Shot CCR**       | [Baiduyun:bxde](https://pan.baidu.com/s/1tKhrIZK7zmpQq3NNCo5Edw?pwd=bxfe)/[OneDrive](https://1drv.ms/u/c/d3b0ec8fe3491f94/ETsFnx-i6sRJvrVrgnvO3h4BMugmO2TUObjD9ddz3xfEmw?e=IoUcXq) | Released |

## 🛠️ Usage

* Clone this repo:

```bash

git clone https://github.com/SCUT-DLVCLab/MegaHan97K.git

```

* Execute the following command to obtain example samples from the MegaHan97K dataset.

```python

python MegaHan_Dataloader.py

```

**Note:**

- The MegaHan97K dataset can only be used for non-commercial research purposes. For scholar or organization who wants to use the MegaHan97K dataset, please first fill in this [Application Form](./application-form/Application-Form-for-Using-MegaHan97K.docx) and sign the [Legal Commitment](./application-form/Legal-Commitment.docx) and email them to us. When submitting the application form to us, please list or attached 1-2 of your publications in the recent 6 years to indicate that you (or your team) do research in the related research fields of handwriting analysis and recognition, document image processing, and so on.

- We will give you the decompression password after your application has been received and approved.

- All users must follow all use conditions; otherwise, the authorization will be revoked.

* To access the entire dataset, please first download it, update the ```data_root``` in the python ```MegaHan_Dataloader.py``` script and then execute

```python

python MegaHan_Dataloader.py

```

## 🌄 Gallery

* **Illustration of the handwritten-original data in MegaHan97K**

![handwo](/images/handw.png)

* **Illustration of the handwritten-augmented data in MegaHan97K**

![handwa](/images/handw_rand.png)

* **Illustration of the M5HisDoc data in MegaHan97K**

![m5](/images/guji.png)

* **Illustration of the Kangxi dictionary data in MegaHan97K**

![kx](/images/kxzd.png)

* **Illustration of the handwritten-original data in MegaHan97K**

![mwo](/images/mwrite.png)

* **Illustration of the handwritten-augmented data in MegaHan97K**

![mwa](/images/mwrite_rand.png)

* **Illustration of the synthetic data in MegaHan97K**

![syn](/images/syn.png)

## 💙 Acknowledgement

- [M5HisDoc](https://github.com/HCIILAB/M5HisDoc)

- [FontDiffuser](https://github.com/yeungchenwa/FontDiffuser)

## License

MegaHan97K should be used and distributed under [Creative Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License](https://creativecommons.org/licenses/by-nc-nd/4.0/) for non-commercial research purposes.

## Copyright

- This repository can only be used for non-commercial research purposes.

- For commercial use, please contact Prof. Lianwen Jin ([email protected]).

- Copyright 2025, [Deep Learning and Vision Computing Lab (DLVC-Lab)](http://www.dlvc-lab.net), South China University of Technology.