Deepesh-001/rodrigo-ocr-model

📜 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.

💻 Usage (Python)

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

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.