Update README.md

README.md

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 # Math-Strike Dataset
-
 ## Dataset Description
-
-**Math-Strike** is a novel dataset featuring real and synthetic strike-outs, component-level annotations, and aligned LaTeX, designed to support research on strike-out removal and handwritten mathematical formula recognition. 
-
-Handwritten STEM manuscripts often contain strike-outs, overwrites, and other markings that disrupt mathematical content structure and reduce OCR/VLM recognition accuracy. This dataset provides a rigorous benchmark for training and evaluating models on connected-component classification, geometry-aware inpainting, and downstream compilable LaTeX generation.
+**Math-Strike** is a novel dataset featuring real and synthetic strike-outs, component-level annotations, and aligned LaTeX, designed to support research on strike-out removal and handwritten mathematical formula recognition. Handwritten STEM manuscripts often contain strike-outs, overwrites, and other markings that disrupt mathematical content structure and reduce OCR/VLM recognition accuracy. This dataset provides a rigorous benchmark for training and evaluating models on connected-component classification, geometry-aware inpainting, and downstream compilable LaTeX generation.
 
 The collection originates from the 2024-2025 mid-term and final examinations of a university's Multivariate Calculus Elite class. 
 
 ### Dataset Subsets
-
 The dataset is divided into two main subsets, easily accessible via Hugging Face's configuration system:
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 - **`real` (Math-Strike-Real)**: Contains only real, authentic strike-outs collected directly from student exam papers.
 - **`synth` (Math-Strike-Synth)**: Contains synthetic strike-outs generated using an augmentation taxonomy of 20 diverse strike-out styles (e.g., wavy, zigzag, multi-crossed, blackout) to address class imbalance and improve model robustness against complex occlusion patterns.
-
 Additionally, the `original_img` folder is provided in the repository, containing the full page-level raw scans with minimal border cropping and all original marks.
 
 ## Dataset Structure
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 ### Data Instances
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 When loading the dataset via the `datasets` library, each instance represents a single connected component extracted from the manuscript.
-
-**Example instance:**
-
-```json
-{
-    "id": 85235,
-    "page_img": "20250523024843071_page001.png",
-    "bbox": [5694, 6677, 91, 112],
-    "centroid": [5739.5, 6733.0],
-    "box_area": 4506,
-    "label": 0,
-    "comp_size": [112, 91],
-    "image": "<...>"
-    "file": "<...>"
-}
-```
-
 ### Data Fields
-
-- **`id`** (int): Global component identifier.
-- **`page_img`** (string): Source page filename.
-- **`bbox`** (list): Bounding box coordinates in pixels.
-- **`centroid`** (list): Geometric centre (x, y) of the component.
-- **`box_area` / `pixel_area`** (int): Foreground-pixel count within the component.
-- **`label`** (int): 0 = retained (valid mathematical symbol), 1 = removed (strike-out/noise).
-- **`comp_size`** (list): Height and width of the bounding box.
-- **`image`** (Image): The actual cropped PNG image of the component.
-- **`file`** (string): The actual path of the image.
+| Field | Type | Description |
+| :--- | :--- | :--- |
+| `id` | int | Global component identifier. |
+| `page_img` | string | Source page filename. |
+| `bbox` | list | Bounding box coordinates in pixels. |
+| `centroid` | list | Geometric centre (x, y) of the component. |
+| `box_area` / `pixel_area` | int | Foreground-pixel count within the component. |
+| `label` | int | 0 = retained (valid mathematical symbol), 1 = removed (strike-out/noise). |
+| `comp_size` | list | Height and width of the bounding box. |
+| `image` | Image | The actual cropped PNG image of the component. |
+| `file` | string | The actual path of the image. |
 
 ## Usage
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 You can easily load the dataset using the Hugging Face `datasets` library. The images and metadata are already pre-aligned in Parquet format.
-
 ```python
 from datasets import load_dataset
 
@@ -80,11 +53,9 @@ train_data[0]["image"].show()
 ```
 
 ## License
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 The Math-Strike dataset is distributed under the **CC-BY-NC 4.0** license for non-commercial research and educational use.
 
 ## Citation
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 If you find this dataset useful for your research, please cite our paper:
 
 ```