| --- |
| license: apache-2.0 |
| task_categories: |
| - text-to-image |
| language: |
| - en |
| tags: |
| - text-rendering |
| - ocr |
| - synthetic-data |
| - generative-models |
| - fine-tuning |
| size_categories: |
| - 1M<n<10M |
| pretty_name: Text Render 2M |
| --- |
| |
| # Text Render 2M Dataset |
|
|
| A large-scale dataset containing 2 million text rendering image-text pairs for training generative models to improve text rendering performance. |
|
|
| ## Dataset Structure |
|
|
| - **`image`**: Rendered text image in PNG format |
| - **`text`**: Corresponding text content |
| - **`file_name`**: Original filename |
| - **`folder_id`**: Folder identifier |
|
|
| ## Usage |
|
|
| This dataset is designed for fine-tuning generative models to improve text rendering capabilities. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("PosterCraft/Text-Render-2M") |
| print(dataset) |
| |
| # Access a sample |
| sample = dataset['train'][0] |
| print(sample['text']) |
| sample['image'].show() |
| ``` |
|
|
| ## Applications |
|
|
| - Fine-tuning text-to-image models for better text rendering |
|
|
| ## License |
|
|
| Apache License 2.0 |
|
|
