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README.md

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+# 🇲🇲 Myanmar Complex Document Layouts
+
+A large-scale, high-quality synthetic dataset containing **17,632 images** of complex document layouts, dashboards, and infographics entirely in the Myanmar (Burmese) language. 
+
+This dataset is specifically designed to train and benchmark modern Computer Vision and multimodal LLMs on complex Myanmar typography, structured data, and diverse graphical layouts.
+
+## 📊 Dataset Overview
+- **Total Images:** 17,632 high-resolution pages.
+- **Language:** Myanmar (Burmese).
+- **Format:** Parquet (Optimized for streaming and fast loading).
+- **Content:** Dictionary definitions, part-of-speech (POS) tagging, phonetics, related word tables, and dynamic graphical charts.
+
+## 🌟 Key Features
+* **Rich Typography:** Utilizes a diverse pool of Myanmar fonts classified into Body, Bold, UI, and Decorative styles.
+* **Complex Layouts:** Alternating 60/40 and 40/60 split-grid layouts featuring multi-line paragraphs, structured data tables, and metric summary boxes.
+* **Diverse Data Visualizations:** Includes 9 different chart categories (Column, Bar, Line, Area, Pie, Donut, Radar, Scatter, Bubble) rendered in 2D, 3D, and Interactive styles.
+* **Perfect Bounding Boxes:** The metadata provides exact pixel-perfect bounding box coordinates (`[left, top, right, bottom]`) for every text element, chart wrapper, and table cell on the page.
+* **Realistic Dimensions:** Rendered in standard A4 and US Letter sizes, covering both Portrait and Landscape orientations.
+
+## 🚀 Primary Use Cases
+1. **Document OCR & Text Extraction:** Training models to accurately read heavily formatted Myanmar text without spacing issues.
+2. **Document Layout Analysis:** Training models like LayoutLM, Donut, or Docling to understand reading order, columns, and spatial relationships.
+3. **Document Visual Question Answering (DocVQA):** Benchmarking multimodal LLMs on their ability to extract facts from Myanmar tables and metric boxes.
+4. **Chart Understanding:** Teaching AI to interpret visual data structures associated with Myanmar labels.
+
+## 🗂️ Metadata Structure
+Each row in the dataset provides the rendered `image` alongside rich JSON metadata, including:
+* `page_number` & `page_size_name`
+* `layout_style` & `theme` colors
+* `fonts_used` (Specific TTF files used for that page)
+* `chart_1_data` & `chart_2_data` (The raw numerical data backing the charts)
+* `entries`: A list of all extracted text strings and their exact bounding boxes.
+* `table_bbox`, `profile_card_bbox`, `chart_bboxes`: Bounding boxes for the major UI containers.
+
+## ⚙️ Creation Process
+This dataset was procedurally generated using Python and a headless Chromium browser engine (Playwright). Dynamic CSS Grid styling, SVG generation, and strict line-breaking rules were utilized to ensure the text and graphics realistically represent modern digital documents and infographics.