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