Release verified Bina 0.2 RizehPizeh 169k checkpoint

.gitattributes

@@ -40,3 +40,5 @@ checkpoints/eval-00004/best_accuracy.pdparams filter=lfs diff=lfs merge=lfs -tex
 checkpoints/eval-00005/best_accuracy.pdparams filter=lfs diff=lfs merge=lfs -text
 checkpoints/eval-00006/best_accuracy.pdparams filter=lfs diff=lfs merge=lfs -text
 checkpoints/eval-00009/best_accuracy.pdparams filter=lfs diff=lfs merge=lfs -text
+Bina-0.2-RizehPizeh.pdparams filter=lfs diff=lfs merge=lfs -text
+inference/inference.pdiparams filter=lfs diff=lfs merge=lfs -text

Bina-0.2-RizehPizeh.pdparams

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:52d01041e2ea9b4575464392d513893ad81452dc6086bc81a077fe15c7017fca
+size 142364527

LICENSE

@@ -0,0 +1,201 @@
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MODEL_PROVENANCE.json

@@ -0,0 +1,55 @@
+{
+  "schema": "bina02.ppocrv6.model-provenance.v1",
+  "model_id": "Reza2kn/Bina-0.2-RizehPizeh",
+  "release": "0.2.0-169k",
+  "base_model": "PaddlePaddle/PP-OCRv6_medium_rec",
+  "architecture": "PP-OCRv6 medium recognition, SVTR_LCNet/PPLCNetV4, CTC",
+  "paddleocr_commit": "2661c7c0ef5c613e8f93c6e93b2e052399f0f854",
+  "dataset_revisions": {
+    "Reza2kn/persian-handwriting-pages-3.69m": "d94db7b55cf2d6521f581f10226bb117d2e0acaf",
+    "Reza2kn/persian-printed-ocr-3.5m": "41c5c977901bdd153b44816bbb92d7d4699524f9"
+  },
+  "training_rows": {
+    "handwriting": 84500,
+    "printed": 84500,
+    "total": 169000
+  },
+  "evaluation_rows": {
+    "handwriting": 2048,
+    "printed": 2048,
+    "total": 4096
+  },
+  "preprocessing": {
+    "input": "content-tight horizontal line crop",
+    "image_shape": [
+      3,
+      48,
+      768
+    ],
+    "padding": false,
+    "tall_crop_rotation": "clockwise_90",
+    "printed_foreground_trim": true,
+    "target_order": "PaddleOCR BaseRecLabelDecode.pred_reverse"
+  },
+  "training": {
+    "batch_size": 16,
+    "learning_rate": 0.0003,
+    "best_step": 47520,
+    "stopped_step": 50160,
+    "early_stop": "three evaluations without 0.0005 NED improvement"
+  },
+  "independent_evaluation": {
+    "exact_lines": 3474,
+    "exact_line_accuracy": 0.84814453125,
+    "mean_normalized_edit_similarity": 0.9880669756561222,
+    "handwriting_exact_line_accuracy": 0.8583984375,
+    "printed_exact_line_accuracy": 0.837890625,
+    "all_transforms_accepted_without_replacement": true
+  },
+  "sha256": {
+    "checkpoint": "52d01041e2ea9b4575464392d513893ad81452dc6086bc81a077fe15c7017fca",
+    "inference_graph": "4f0c41b21815a2e2b5765009d3a15efc1a5850032a9c6e6694325ee2",
+    "inference_parameters": "4f84e43243e9bb2a6b5617da2a22c071f5ebf2db489c1fb55d7e3dd1e2dc99e3",
+    "dictionary": "28fb97acc0feca48f8243d36f8c3ea80efda25c13c29db1c41002900310b6c8e"
+  }
+}

PADDLEOCR_COMMIT

@@ -0,0 +1 @@
+2661c7c0ef5c613e8f93c6e93b2e052399f0f854

README.md

@@ -1,26 +1,111 @@
+---
+license: apache-2.0
+language:
+- fa
+library_name: paddleocr
+pipeline_tag: image-to-text
+base_model: PaddlePaddle/PP-OCRv6_medium_rec
+datasets:
+- Reza2kn/persian-handwriting-pages-3.69m
+- Reza2kn/persian-printed-ocr-3.5m
+tags:
+- ocr
+- persian
+- handwriting
+- printed-text
+- paddlepaddle
+- pp-ocrv6
+---
+
 # Bina 0.2 - RizehPizeh
 
-Persian full-page OCR pipeline based on PP-OCRv6:
+Bina 0.2 - RizehPizeh is a compact Persian line-recognition model fine-tuned
+from PP-OCRv6 medium recognition. It recognizes both handwritten and printed
+Persian text using a 161-symbol character dictionary and a CTC decoder.
+
+This repository preserves the earlier experimental checkpoints under
+`checkpoints/`. The verified release is at the repository root.
+
+## Verified release
+
+| Held-out split | Rows | Exact lines | Exact-line accuracy | Mean normalized edit similarity |
+| --- | ---: | ---: | ---: | ---: |
+| Combined | 4,096 | 3,474 | **84.81%** | **98.81%** |
+| Handwriting | 2,048 | 1,758 | **85.84%** | **98.83%** |
+| Printed | 2,048 | 1,716 | **83.79%** | **98.79%** |
+
+Exact-line accuracy is strict: one incorrect character, digit, space, or
+punctuation mark makes the entire line incorrect. The independent evaluator
+accepted all 4,096 transforms without replacement.
+
+## Package contents
+
+- `inference/`: exported Paddle inference graph and parameters.
+- `bina_text_recognition.py`: logical-order Persian inference wrapper.
+- `Bina-0.2-RizehPizeh.pdparams`: best training checkpoint.
+- `config.yml`: portable architecture and preprocessing configuration.
+- `persian_arabic_bina02_dict.txt`: 161-symbol character dictionary.
+- `MODEL_PROVENANCE.json`: revisions, counts, metrics, and SHA-256 hashes.
+- `eval-aligned-row-analysis-v2.json`: independent row-level evaluation.
+
+## Inference
+
+Install the appropriate PaddlePaddle build for your hardware, then:
+
+```bash
+pip install "paddleocr>=3.3.0,<4"
+git clone https://huggingface.co/Reza2kn/Bina-0.2-RizehPizeh
+cd Bina-0.2-RizehPizeh
+python bina_text_recognition.py path/to/line.jpg --device cpu
+```
+
+Or use it from Python:
+
+```python
+from bina_text_recognition import BinaTextRecognition
+
+model = BinaTextRecognition("inference", device="cpu")
+for result in model.predict("line.jpg"):
+    print(result["text"], result["score"])
+```
+
+The exported CTC model emits Persian in visual order. Use the included wrapper
+to recover logical reading order while preserving Latin and numeric runs.
+
+## Input contract
+
+The recognizer expects a horizontal, content-tight line crop:
+
+- Rotate tall detector crops 90 degrees clockwise.
+- Remove excessive printed-image background while retaining a small margin.
+- Resize to `3 x 48 x 768` with `padding: false`.
+- Preserve ZWNJ and Persian digits.
+
+For full-page OCR, pair this recognizer with
+[`PaddlePaddle/PP-OCRv6_medium_det_safetensors`](https://huggingface.co/PaddlePaddle/PP-OCRv6_medium_det_safetensors),
+rectify and normalize each detected crop, recognize each line, then reconstruct
+the page in reading order. This repository contains the recognizer, not the
+detector.
+
+## Training
 
-1. Detect ordered Persian text regions.
-2. Recognize CTC-safe RTL word groups.
-3. Reconstruct lines and complete pages in reading order.
+The verified release used 169,000 balanced training lines:
 
-## Current training state
+- 84,500 teacher-aligned handwriting crops.
+- 84,500 printed line images.
+- 4,096 page-isolated held-out evaluation lines.
 
-The initial PP-OCRv6 medium recognizer pilot reached a held-out normalized edit
-similarity of `0.1752708888` before its ephemeral Colab runtime reset. No model
-checkpoint survived that reset.
+Training stopped automatically after validation plateaued. The best checkpoint
+was selected around step 47,520. Dataset revisions and preprocessing details
+are pinned in `MODEL_PROVENANCE.json`.
 
-The files under `training-kit/` reproduce data preparation, RTL segmentation,
-and evaluation-driven early stopping. Future best checkpoints are uploaded
-under `checkpoints/` so runtime resets do not erase training progress.
+## Limitations
 
-## Data
+- Persian-focused; other-language performance was not preserved or evaluated.
+- Full-page use requires a separate detector and reading-order reconstruction.
+- The handwriting split is teacher-aligned and may contain residual label noise.
+- Very small isolated symbols and unusually degraded crops remain difficult.
 
-- `Reza2kn/persian-handwriting-pages-3.69m`
-- `Reza2kn/persian-printed-ocr-3.5m`
-- `Reza2kn/visualears-hardword-sentences` for rare-character coverage
+## License
 
-The Persian recognizer uses a character dictionary rather than a language-model
-tokenizer.
+Apache License 2.0. See `LICENSE`.

bina_text_recognition.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python3
+"""Logical-order Persian inference for Bina 0.2 - RizehPizeh."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import re
+from pathlib import Path
+from typing import Any, Iterator
+
+from paddleocr import TextRecognition
+
+
+_LTR_RUN = re.compile(r"[a-zA-Z0-9 :*./%+-]")
+
+
+def pred_reverse(text: str) -> str:
+    """Match PaddleOCR's Arabic-aware BaseRecLabelDecode.pred_reverse."""
+    segments: list[str] = []
+    current_ltr = ""
+    for character in text:
+        if _LTR_RUN.search(character):
+            current_ltr += character
+            continue
+        if current_ltr:
+            segments.append(current_ltr)
+            current_ltr = ""
+        segments.append(character)
+    if current_ltr:
+        segments.append(current_ltr)
+    return "".join(reversed(segments))
+
+
+class BinaTextRecognition:
+    """Run the exported Paddle model and return logical-order Persian text."""
+
+    def __init__(
+        self,
+        model_dir: str | Path | None = None,
+        device: str | None = None,
+    ) -> None:
+        if model_dir is None:
+            model_dir = Path(__file__).resolve().parent / "inference"
+        options: dict[str, Any] = {"model_dir": str(model_dir)}
+        if device is not None:
+            options["device"] = device
+        self._model = TextRecognition(**options)
+
+    def predict(
+        self,
+        input: str | Path | list[str] | list[Path],
+        batch_size: int = 1,
+    ) -> Iterator[dict[str, Any]]:
+        for result in self._model.predict(input=input, batch_size=batch_size):
+            payload = result.json
+            if callable(payload):
+                payload = payload()
+            raw = payload["res"]
+            visual_text = str(raw["rec_text"])
+            yield {
+                "input_path": raw.get("input_path"),
+                "text": pred_reverse(visual_text),
+                "score": float(raw["rec_score"]),
+                "raw_visual_text": visual_text,
+            }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("images", nargs="+")
+    parser.add_argument(
+        "--model-dir",
+        default=str(Path(__file__).resolve().parent / "inference"),
+    )
+    parser.add_argument("--device", default=None)
+    parser.add_argument("--batch-size", type=int, default=1)
+    args = parser.parse_args()
+
+    model = BinaTextRecognition(args.model_dir, device=args.device)
+    for prediction in model.predict(args.images, batch_size=args.batch_size):
+        print(json.dumps(prediction, ensure_ascii=False))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

config.yml

@@ -0,0 +1,78 @@
+Global:
+  model_name: PP-OCRv6_medium_rec
+  debug: false
+  use_gpu: true
+  epoch_num: 12
+  log_smooth_window: 20
+  print_batch_step: 20
+  save_model_dir: ./output
+  save_epoch_step: 1
+  eval_batch_step:
+  - 0
+  - 2640
+  cal_metric_during_train: false
+  pretrained_model: ./Bina-0.2-RizehPizeh
+  checkpoints: null
+  save_inference_dir: ./inference
+  use_visualdl: false
+  infer_img: doc/imgs_words/ch/word_1.jpg
+  character_dict_path: ./persian_arabic_bina02_dict.txt
+  max_text_length: 128
+  infer_mode: false
+  use_space_char: true
+  distributed: false
+  save_res_path: /home/rezo/bina02-ppocr/clean-restart/runs/bina02-169k-cropnorm-cw-bs16-v1/predicts.txt
+  d2s_train_image_shape:
+  - 3
+  - 48
+  - 768
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  lr:
+    name: Cosine
+    learning_rate: 0.0003
+    warmup_epoch: 0
+  regularizer:
+    name: L2
+    factor: 0.0
+Architecture:
+  model_type: rec
+  algorithm: SVTR_LCNet
+  Transform: null
+  Backbone:
+    name: PPLCNetV4
+    model_size: medium
+    train_pool_width: 96
+    force_pool_width: true
+  Head:
+    name: MultiHead
+    head_list:
+    - CTCHead:
+        Neck:
+          name: lightsvtr
+          dims: 192
+          depth: 2
+          mlp_ratio: 4.0
+          local_kernel: 7
+          use_guide: false
+        Head:
+          fc_decay: 1.0e-05
+    - NRTRHead:
+        nrtr_dim: 512
+        max_text_length: 128
+Loss:
+  name: MultiLoss
+  weight_1: 1.0
+  weight_2: 0.0
+  loss_config_list:
+  - CTCLoss: null
+  - NRTRLoss: null
+PostProcess:
+  name: CTCLabelDecode
+Metric:
+  name: RecMetric
+  main_indicator: norm_edit_dis
+  ignore_space: false
+profiler_options: null

inference/inference.pdiparams

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f84e43243e9bb2a6b5617da2a22c071f5ebf2db489c1fb55d7e3dd1e2dc99e3
+size 62146801

inference/inference.yml

@@ -0,0 +1,205 @@
+Global:
+  model_name: PP-OCRv6_medium_rec
+Hpi:
+  backend_configs:
+    paddle_infer:
+      trt_dynamic_shapes: &id001
+        x:
+        - - 1
+          - 3
+          - 48
+          - 160
+        - - 1
+          - 3
+          - 48
+          - 320
+        - - 8
+          - 3
+          - 48
+          - 3200
+    tensorrt:
+      dynamic_shapes: *id001
+PreProcess:
+  transform_ops:
+  - DecodeImage:
+      channel_first: false
+      img_mode: BGR
+  - MultiLabelEncode:
+      gtc_encode: NRTRLabelEncode
+  - RecResizeImg:
+      image_shape:
+      - 3
+      - 48
+      - 768
+      padding: false
+  - KeepKeys:
+      keep_keys:
+      - image
+      - label_ctc
+      - label_gtc
+      - length
+      - valid_ratio
+PostProcess:
+  name: CTCLabelDecode
+  character_dict:
+  - '!'
+  - '"'
+  - '#'
+  - '%'
+  - '&'
+  - ''''
+  - (
+  - )
+  - '*'
+  - +
+  - ','
+  - '-'
+  - .
+  - /
+  - '0'
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normalization-report.json

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persian_arabic_bina02_dict.txt

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requirements.txt

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+paddleocr>=3.3.0,<4

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