---
license: apache-2.0
tags:
- paddleocr
- ocr
- vision-language-model
- ernie-kit
- historical-document-processing
- handwriting-recognition
- gothic-script
- paleography
base_model: PaddlePaddle/PaddleOCR-VL-0.9B
language:
- es
pipeline_tag: image-to-text
---

# 📜 Chronos-VL: The 1545 Resurrection Engine

> **🏆 Baidu ERNIE AI Developer Challenge Submission**

**Chronos-VL** is a specialized fine-tune of **PaddleOCR-VL-0.9B**, engineered to decipher Early Modern Spanish Gothic script (c. 1545). Trained on the **RODRIGO Corpus** using Baidu's **ERNIEKit** on an NVIDIA A100 GPU, this model bridges the 500-year gap between ancient archives and modern AI.

While standard OCR models fail on these historical manuscripts due to complex calligraphy, ligatures, and ink degradation, Chronos-VL achieves near-perfect transcription for clear text lines.

## 📊 Performance Benchmark

We conducted a side-by-side evaluation on 100 unseen historical samples using a custom A/B testing framework.

| Metric | Baseline (Standard PaddleOCR) | Chronos-VL (Ours) | Improvement |
| :--- | :--- | :--- | :--- |
| **Median Character Error Rate (CER)** | 19.82% | **1.64%** | **12x Better** |
| **Excellent Predictions (<5% Error)** | 1% | **77%** | **76x Increase** |
| **Word Error Rate (WER)** | 74.44% | **17.35%** | **4x Better** |


## 🚀 Interactive Demo (Colab)

Don't just take our word for it. Run the **Chronos System** yourself. 
Our interactive Gradio app allows you to:
1.  **Compare** Baseline vs. Chronos-VL side-by-side.
2.  **Visualize** the "X-Ray" overlay (Visual Restoration).
3.  **Translate** the archaic text to Modern Spanish and English.

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/12ccCTTvJc9G6AfyvGPg0pG528bCXelaK?usp=sharing)

## 💻 Usage (Python)

To use this model in your own code, you need `paddleocr` and `huggingface_hub`.

```python
from huggingface_hub import snapshot_download
from paddleocr import PaddleOCR

# 1. Download the Fine-Tuned Weights
local_dir = snapshot_download(repo_id="Deepesh-001/rodrigo-ocr-model")

# 2. Initialize the Engine
# We use use_angle_cls=True to handle rotated manuscript lines
ocr = PaddleOCR(
    rec_model_dir=local_dir, 
    use_angle_cls=True, 
    use_gpu=True
)

# 3. Run Inference on a 1545 Manuscript
image_path = "rodrigo_sample.png"
result = ocr.ocr(image_path, cls=True)

for line in result[0]:
    text = line[1][0]
    confidence = line[1][1]
    print(f"Detected: {text} | Confidence: {confidence:.2f}")
```

## 🧠 The Chronos Pipeline (System Design)

This model is the core perception layer of the broader **Chronos System**:

1.  **Visual Perception (AI):** Chronos-VL extracts raw Gothic text (e.g., *"dixo estonces"*).
2.  **Semantic Normalization (Logic):** A post-processing engine normalizes Archaic Castilian spelling to Modern Spanish (e.g., *"dijo entonces"*).
3.  **Global Access (Translation):** Automated translation to English, making Spanish heritage accessible to non-Spanish speakers.

## 📂 Dataset Info
Trained on the **RODRIGO Corpus** (Spanish State Archives).
- **Era:** 1545
- **Script:** Gothic Cursive
- **Size:** 9,000 text lines (80/20 Split)
- **Format:** Page-XML converted to ERNIEKit JSONL

## 🔗 Links
- **Code Repository:** [ https://github.com/deepeshahlawat/Chronos-VL ]
- **Project Video:** [https://www.youtube.com/watch?v=PaK24VT_3Jk]

*Built with ❤️ using PaddlePaddle and ERNIEKit.*