Versatile-OCR-Program
Multi-modal OCR pipeline optimized for ML training (text, figure, math, tables, diagrams).
raphael-seo/Versatile-OCR-Program is ranked 15,158 with 675 stars.
raphael-seo/Versatile-OCR-Program is ranked 15,158 among these 8 peers; xming521/CTAI is ranked 15,161.
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| Parameter | Value |
|---|---|
| Language | Python |
| Category | Applications |
| Subcategory | Object detection |
| Keywords | Multimodal, OCR |
| Stars | 675 |
| Forks | 49 |
| Contributors | 1 |
| Created date | 2025-04-01 |
| Updated date | 2026-10-14 |
| Stars in 1 day | 0 |
| Stars in 7 days | -1 |
| Rank | 15,158 |
| Previous rank | 14,980 |
| Rank change | -178 |
| 7-day stars rank | 17,739 |
| Previous 7-day stars rank | 17,691 |
| 7-day stars rank change | -48 |
| Total stars rank | 15,306 |
| Previous total stars rank | 15,277 |
| Total stars rank change | -29 |
| Country | South Korea |
0) are preserved under for reference but not maintained. UPDATE: Release Slightly Delayed First of all, thank you so much for your interest in this project. I had originally planned to release the first version of the AI pipeline before June. Rather than rushing out something incomplete, I’ve decided to take a bit more time to ensure the release is genuinely useful, stable, and worth your time. I didn't expect it to get this much attention, so thanks. Since
I'm the first user, I want to make sure it's something I’d actually want to use before releasing it. Development will resume after the exam, and the public release will follow once the system is truly ready. It supports multilingual text, mathematical formulas, tables, diagrams, and charts, making it ideal for creating high-quality training datasets. Key Features – Optimized for ML Training: Extracted elements such as diagrams, tables, and figures are semantically annotated with contextual explanations. This includes automatic
generation of natural language descriptions for visual content (e. , “This figure shows the process of mitosis in four stages”) to enhance downstream model training. – Multilingual Support: Works with Japanese, Korean, and English, and can be easily customized for additional languages. – Structured Output: Generates AI-ready outputs in JSON or Markdown, including human-readable descriptions of mathematical expressions, table summaries, and figure captions. – High Accuracy: Achieves over 90–95% accuracy on real-world academic datasets such as EJU Biology and UTokyo
Math. – Complex Layout Support: Accurately processes exam-style PDFs with dense scientific content, formula-heavy paragraphs, and rich visual elements. – Built With: DocLayout-YOLO, Google Vision API, Gemini Pro Vision, MathPix OCR, OpenAI API, OpenCV, and more. Sample Outputs Below are actual examples of outputs generated by this system using real-world materials (2017 EJU Biology & 2014 University of Tokyo Math), including English-translated semantic context and extracted data. **Math Input** **Output** **English-translated outputs** Question 1. Consider the rectangular
prism OABC–DEFG with a square base of side length 1. Points P, Q, R are on the segments AE, BF, and CG, respectively, and four points O, P, Q, and R lie on the same plane. Let S be the area of quadrilateral OPQR. (2) If α + β = 1 and S = S, find the value of tan α + tan β. Also, if α ≤ β, find the value of tan α. [Image Start] Image description: This image shows the rectangular prism OAB–CDEFGQ. The plane ORPQ intersects
the prism and is highlighted. Line RC lies on face ODCG, and line PB lies on face ABFQ. Educational value: This image enhances spatial reasoning by visualizing 3D geometry and cross-sections. It helps learners understand concepts such as plane geometry, solid shapes, spatial visualization, and angles. Related topics: Solid geometry, cross-sections, prism faces, triangle, spatial reasoning Exam relevance: This type of question appears in entrance exams like: 1. Calculate the area of ORPQ using angle α 2. Determine the
angle between ORPQ and the prism's face 4. Locate points P, Q, R in coordinate space 5. Calculate volume/area
How many stars and forks are recorded?
raphael-seo/Versatile-OCR-Program has 675 stars and 49 forks.
What is the repository rank?
raphael-seo/Versatile-OCR-Program is ranked 15,158.
What language and category are recorded?
raphael-seo/Versatile-OCR-Program has 675 stars, uses Python and belongs to Applications.
Which repository is closest in rank?
raphael-seo/Versatile-OCR-Program is compared with xming521/CTAI, ranked 15,161 with 675 stars.