| --- |
| language: bn |
| license: mit |
| tags: [ocr, bengali, crnn, easyocr, ctc] |
| datasets: [mnsm92/bengali-ocr-dataset-1m] |
| metrics: [cer, wer] |
| --- |
| |
| # Bengali CRNN OCR — Custom EasyOCR Recognition Model |
|
|
| **DocReader BD — CSC4233 NLP Final Project, AIUB** |
|
|
| ## Results |
|
|
| | Model | CER ↓ | WER ↓ | Char Accuracy | |
| |---|---|---|---| |
| | Tesseract (baseline) | ~0.45 | ~0.60 | ~55% | |
| | EasyOCR default | ~0.25 | ~0.40 | ~75% | |
| | **BengaliCRNN (ours)** | **0.0348** | **0.1020** | **96.5%** | |
|
|
| ## Architecture |
| ResNet34 (grayscale) + 2× BiLSTM (hidden=256) + CTC loss |
| Vocab: 152 Bengali + English chars | Input: 64×200px |
|
|
| ## Files |
| - `bengali_crnn.pth` — EasyOCR-ready weights (module. prefix) |
| - `phase1_best.pth` — clean weights for further training |
| - `bengali_crnn.py` — EasyOCR network definition |
| - `bengali_crnn.yaml` — EasyOCR config |
| - `vocab.json` — character vocabulary |
| - `config.json` — model config |
|
|
| ## Usage |
| ```python |
| import easyocr |
| reader = easyocr.Reader( |
| lang_list=["bn"], |
| recog_network="bengali_crnn", |
| model_storage_directory="./bengali_ocr_model", |
| user_network_directory="./bengali_ocr_model", |
| gpu=True |
| ) |
| results = reader.readtext("bengali_doc.jpg") |
| ``` |
|
|
