| --- |
| license: apache-2.0 |
| task_categories: |
| - image-to-text |
| language: |
| - en |
| tags: |
| - image |
| - text |
| - document |
| - pdf |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # **OpenDoc-Pdf-Preview** |
|
|
| **OpenDoc-Pdf-Preview** is a compact visual preview dataset containing 6,000 high-resolution document images extracted from PDFs. This dataset is designed for **Image-to-Text** tasks such as document OCR pretraining, layout understanding, and multimodal document analysis. |
|
|
| ## Dataset Summary |
|
|
| * **Modality:** Image-to-Text |
| * **Content Type:** PDF-based document previews |
| * **Number of Samples:** 6,000 |
| * **Language:** English |
| * **Format:** Parquet |
| * **Split:** `train` only |
| * **Size:** 606 MB |
| * **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) |
|
|
| *Each entry consists of:* |
|
|
| * A **preview image** of a PDF page |
| * A placeholder column named `pdf` (currently appears empty or reserved for future metadata) |
|
|
| ## Use Cases |
|
|
| * Pretraining OCR or Document Layout models |
| * PDF snapshot-based search indexing |
| * Few-shot document vision evaluation |
| * Visual prompt tuning for vision-language models (VLMs) |
|
|
| ## How to Use |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("prithivMLmods/OpenDoc-Pdf-Preview", split="train") |
| ``` |
|
|
| ## Notes |
|
|
| * The column `pdf` may be extended in future versions with associated metadata or textual content. |
| * Each sample preview is rendered from the original PDF file, representing various real-world layouts and formats. |
