🔤 Chinese Text Recognition Demo
Compare Original vs Fine-tuned PaddleOCR models side-by-side!
Upload an image to see the improvements from fine-tuning
📤 Upload Image
📋 Try Sample Images
Click on a sample image to test
📊 Model Comparison Results
Original Model Results
Fine-tuned Model Results
📊 Model Comparison Analysis
📝 1. Recognition Results
Original Model: ``
Fine-tuned Model: ``
📊 2. Confidence Scores
Original Model: 0.000 (0.0%)
Fine-tuned Model: 0.000 (0.0%)
Change: 🟡 0.000 (similar confidence)
✅ 3. Text Match
🎯 Both models produced identical text recognition
🎯 Overall Assessment
🟡 Good: Consistent performance across models
💡 Note: Fine-tuning typically improves performance on domain-specific text and characters similar to the training data.
ℹ️ About This Demo
This demo compares Original PaddleOCR vs Fine-tuned PaddleOCR models side-by-side to showcase the improvements from fine-tuning.
Key Features:
- 🔄 Side-by-Side Comparison: See both models' results simultaneously
- 📊 Confidence Analysis: Compare confidence scores between models
- 🎯 Improvement Metrics: Quantify the benefits of fine-tuning
- 🔍 Detailed Breakdown: Segment-by-segment comparison analysis
- 📈 Performance Insights: Understand when fine-tuning helps most
Model Details:
- Original Model: Standard PP-OCRv5 Server Recognition
- Fine-tuned Model: Trained on 400K additional Chinese text images
- Character Set: 4,865 unique Chinese characters
- Training Data: Domain-specific Chinese text patterns
Tips for Best Results:
- Use clear, well-lit images with visible Chinese text
- Try images with characters similar to the training data
- Single-line text often shows clearest improvements
- Compare results on various text complexities
🎯 The comparison will show you exactly how fine-tuning improves text recognition performance!