Update README.md

README.md

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+# ShobdoOCR — Bangla-English OCR for Bangladeshi Documents
+
+ShobdoOCR is a word-level OCR system designed for Bangladeshi government documents including NID cards, birth certificates, land deeds, and invoices. It handles mixed Bengali and English text using a classifier-first dual-recognizer architecture — a lightweight 23K-parameter script classifier (99.82% accuracy) routes each detected word to either a Bengali CRNN or English CRNN recognizer, returning per-word bounding boxes, recognized text, and script labels.
+
+Part of the **DocReader BD** intelligent document understanding system.
+
 ---
-language: bn
-license: mit
-tags:
-  - object-detection
-  - ocr
-  - bengali
-  - yolov8
+
+## Install
+
+```bash
+pip install --index-url https://test.pypi.org/simple/ \
+            --extra-index-url https://pypi.org/simple/ \
+            shobdoocr==0.1.1
+```
+> Note: shobdoocr is currently hosted on TestPyPI (test registry).
+> Dependencies are fetched from the official PyPI automatically.
+
 ---
 
-# ShobdoOCR — Word-Level Detection
+## Usage
 
-**Load:**
 ```python
-from ultralytics import YOLO
-from huggingface_hub import hf_hub_download
-model = YOLO(hf_hub_download("Sarjinkhan2003/shobdo-ocr-detection", "shobdo_det.pt"))
-results = model.predict("doc.jpg", conf=0.25)
-```
+from shobdoocr import OCR
+
+ocr = OCR()  # models download automatically (~80MB)
+
+# Plain text
+text = ocr.read_text("nid_card.jpg")
+print(text)
 
-**mAP@0.5:** 0.9840
+# Word-level output with bounding boxes and script labels
+results = ocr.read("nid_card.jpg")
+for word in results:
+    print(word['text'], word['script'], word['box'])
+```