| --- |
| license: apache-2.0 |
| language: |
| - en |
| - ko |
| tags: |
| - handwriting |
| - mathematical-expression-recognition |
| - preprocessing |
| - stroke-grouping |
| - geometry |
| library_name: aiflow-math-ink |
| pipeline_tag: image-to-text |
| --- |
| |
| # AIFlow Math Ink 0.5 |
|
|
| AIFlow Math Ink 0.5 is a **model-agnostic geometric gridding layer** for online |
| handwritten mathematics. It converts ordered pen strokes into spatially coherent |
| formula cells and renders one clean image per cell. |
|
|
| > This repository contains no OCR model, model weight, tokenizer, training data, |
| > or generated prediction. It is a deterministic preprocessing layer only. |
|
|
| The output images can be passed to any image-to-LaTeX recognizer. They are |
| interface-compatible with TexTeller-style image batches, but TexTeller is not |
| included, redistributed, modified, or required by this repository. |
|
|
|  |
|
|
| ## Why this layer exists |
|
|
| An image-to-LaTeX model normally expects one coherent expression image. A pen |
| canvas may instead contain multiple rows, detached superscripts, fractions, or |
| matrix delimiters. AIFlow Math Ink 0.5 uses the original stroke geometry to |
| partition that canvas before recognition. |
|
|
| The layer: |
|
|
| 1. validates bounded UTF-8 JSON-like stroke events; |
| 2. computes width-aware stroke bounding boxes; |
| 3. estimates a scale from the median stroke height; |
| 4. creates same-baseline and local-attachment edges; |
| 5. adds structural bridge edges for fraction bars and tall delimiters; |
| 6. extracts connected components with a disjoint-set structure; |
| 7. sorts cells in stable two-dimensional reading order; and |
| 8. re-renders only the member strokes of each cell. |
|
|
| This is a transparent heuristic algorithm, not a trained neural-network layer. |
|
|
| ## Installation |
|
|
| ```bash |
| pip install Pillow |
| ``` |
|
|
| Clone this repository and add `src` to your Python path, or install it locally: |
|
|
| ```bash |
| pip install -e . |
| ``` |
|
|
| ## Minimal example |
|
|
| ```python |
| from PIL import Image |
| |
| from aiflow_math_ink_05 import GridConfig, Stroke, build_formula_grids, render_grid_images |
| |
| strokes = [ |
| Stroke(0, ((24, 20), (36, 20)), 3.0), |
| Stroke(1, ((10, 42), (60, 42)), 3.0), |
| Stroke(2, ((24, 64), (36, 64)), 3.0), |
| ] |
| |
| grids = build_formula_grids(strokes, GridConfig()) |
| images = render_grid_images(Image.new("RGB", (80, 90), "white"), strokes, grids) |
| |
| for grid, image in zip(grids, images, strict=True): |
| print(grid.stroke_ids) |
| image.save(f"cell-{grid.index}.png") |
| ``` |
|
|
| For an existing API payload, use `parse_writing_events()` before |
| `build_formula_grids()`. See [`examples/basic.py`](examples/basic.py). |
|
|
| ## Recognizer compatibility |
|
|
| `render_grid_images()` returns ordinary RGB `PIL.Image.Image` objects. A |
| recognizer can consume the list as a batch without importing this package into |
| its model implementation. TexTeller compatibility means only this image-level |
| interface; no TexTeller component is included. |
|
|
| ## Method and complexity |
|
|
| The complete method, equations, assumptions, and limitations are documented in |
| [`docs/METHOD.md`](docs/METHOD.md). |
|
|
| For \(n\) accepted strokes, pair construction is \(O(n^2)\), disjoint-set |
| operations are effectively near-linear, and rendering is proportional to the |
| number of retained points plus output pixels. Input caps are mandatory in |
| server environments; the parser defaults to 2,000 strokes and 200,000 total |
| points. |
|
|
| ## Scope and limitations |
|
|
| - This release performs geometry-based grouping, not symbol recognition. |
| - It does not infer LaTeX, semantics, or correctness. |
| - Thresholds are scale-adaptive but remain heuristic. |
| - Dense overlapping notes and unusual layouts can over-merge. |
| - The method has not been presented here as a peer-reviewed contribution. |
| - The repository ships no dataset and makes no benchmark claim. |
|
|
| ## License |
|
|
| The original code in this repository is licensed under Apache License 2.0. |
| Pillow is an install-time dependency and is not vendored. External recognizers |
| are separate works governed by their own licenses. |
|
|
|
|
