| language: bn | |
| license: mit | |
| tags: | |
| - object-detection | |
| - ocr | |
| - bengali | |
| - yolov8 | |
| - word-detection | |
| metrics: | |
| - map | |
| # Bengali OCR — Word-Level Detection (v3) | |
| **Architecture:** YOLOv8n | **Task:** Word-level bounding box detection | |
| ## Results | |
| | mAP@0.5 | Precision | Recall | | |
| |---|---|---| | |
| | 0.9223 | 0.9533 | 0.8722 | | |
| ## Training data | |
| - ICDAR 2019 MLT Bengali (real word boxes) | |
| - 6,000 synthetic printed pages (NID/form/paragraph style) | |
| ## Usage | |
| ```python | |
| from ultralytics import YOLO | |
| from huggingface_hub import hf_hub_download | |
| path = hf_hub_download("Sarjinkhan2003/bengali-ocr-detection", "bengali_det.pt") | |
| model = YOLO(path) | |
| results = model.predict("doc.jpg", conf=0.25) | |
| for box in results[0].boxes: | |
| print(box.xyxy[0].tolist()) # one word per box | |
| ``` | |