---
language:
  - el
tags:
  - ocr
  - htr
  - paddleocr
  - greek
  - handwritten-text-recognition
  - handwriting
  - text-recognition
  - image-to-text
  - onnx
pipeline_tag: image-to-text
library_name: onnxruntime
license: apache-2.0
widget:
- src: https://huggingface.co/iordanissap/handwritten-greek-ocr/resolve/main/test_images/test_text1.jpeg
  example_title: Greek Handwriting Example
---

# Handwritten Greek OCR

An ONNX model for recognizing handwritten Greek text, fine-tuned from PaddlePaddle's PP-OCRv5 server-grade recognition checkpoint. This fine-tune adapts it specifically to the Greek alphabet.

The model was trained on a synthetic dataset of 50,000 images generated using handwritten Greek fonts and containing up to 50 characters (including spaces).

---

## Examples

| Input Image | Predicted Text | Confidence |
| :--- | :--- | :---: |
| <img src="./test_images/test_text1.jpeg" width="250" alt="example 1"/> | η διαδικασία είναι περίπλοκη | 0.9450 |
| <img src="./test_images/test_text2.jpeg" width="250" alt="example 2"/> | η διαδικασία είναι περίπλοκη | 0.9595 |
| <img src="./test_images/test_names_with_comma1.jpeg" width="250" alt="example 3"/> | Ο Γιώργος ο Γιάννης (missed the comma)| 0.8893 |
| <img src="./test_images/test_names_with_comma2.jpeg" width="250" alt="example 3"/> | Ο Γιώργος, ο Γιάννης | 0.9575 |
---

## Input & Preprocessing

- **Color format**: BGR (converted from RGB to match PaddleOCR training convention)
- **Resize**: image is scaled to height `48px`, width padded to `320px` with zeros
- **Normalization**: pixel values normalized to `[-1, 1]`

---

## Limitations

- Designed for **single text-line** images — for multi-line documents, segment lines before running inference.
- Can mostly recognise **Greek characters** and punctuation .


---

## Quick Start

### Installation
```bash
pip install onnxruntime pillow numpy
# For GPU support:
pip install onnxruntime-gpu pillow numpy
```

### Inference
```python
from PIL import Image
import numpy as np
import math
import onnxruntime as ort

def resize_norm_img(img, imgH=48, imgW=320):
    h, w = img.shape[:2]
    ratio = w / float(h)
    resized_w = imgW if math.ceil(imgH * ratio) > imgW else int(math.ceil(imgH * ratio))
    pil_img = Image.fromarray(img)
    resized_image = np.array(pil_img.resize((resized_w, imgH), Image.BILINEAR)).astype('float32')
    resized_image = resized_image.transpose((2, 0, 1)) / 255.0
    resized_image = (resized_image - 0.5) / 0.5
    padding_im = np.zeros((3, imgH, imgW), dtype=np.float32)
    padding_im[:, :, :resized_w] = resized_image
    return np.expand_dims(padding_im, axis=0)

def load_dict(dict_path):
    with open(dict_path, "rb") as f:
        lines = f.readlines()
    character = [line.decode('utf-8').strip() for line in lines] + [" "]
    return ['<blank>'] + character

def decode(preds, character):
    preds_idx = preds.argmax(axis=2)[0]
    preds_prob = preds.max(axis=2)[0]
    char_list, conf_list = [], []
    for i, idx in enumerate(preds_idx):
        if idx != 0 and not (i > 0 and idx == preds_idx[i - 1]):
            char_list.append(character[idx])
            conf_list.append(preds_prob[i])
    text = ''.join(char_list)
    confidence = float(np.mean(conf_list)) if conf_list else 0.0
    return text, confidence

# Load model and dictionary
session = ort.InferenceSession("model.onnx", providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
characters = load_dict("greek_dict.txt")

# Run on an image
img = np.array(Image.open("your_image.png").convert("RGB"))
img_bgr = img[:, :, ::-1]  # RGB → BGR
input_tensor = resize_norm_img(img_bgr)

outputs = session.run(None, {session.get_inputs()[0].name: input_tensor})
text, confidence = decode(outputs[0], characters)

print(f"Recognized: {text}")
print(f"Confidence: {confidence:.4f}")
```

---

## Model Details

| Property | Value |
|---|---|
| **Task** | Handwritten Greek text recognition |
| **Architecture** | SVTR_HGNet (PPHGNetV2_B4 backbone + SVTR neck, CTC head)  |
| **Format** | ONNX |
| **Input size** | `3 × 48 × 320` (C × H × W) |
| **Language** | Greek (`el`) |
| **Runtime** | ONNX Runtime (CPU & CUDA) |

---

## Repository Files
```
├── model.onnx        # ONNX model weights
├── greek_dict.txt    # Greek character dictionary
├── inference.py      # Ready-to-run inference script
└── test.png          # Sample test image
```

---

## Citation

If you use this model, please cite this repository:
```bibtex
@misc{handwritten-greek-ocr,
  title  = {Handwritten Greek OCR},
  author = {Iordanis Sapidis},
  year   = {2026},
  url    = {https://huggingface.co/iordanissap/handwritten-greek-ocr}
}
```