38 lines
1.5 KiB
Markdown
38 lines
1.5 KiB
Markdown
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# Evaluation Results Summary
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## Quick Overview
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- **Dataset**: 56 document samples
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- **Best Approach**: Crop (No Shadow Removal)
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- **Performance Gain**: +14.1% F1-score improvement over baseline
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## Performance Comparison (Ranked from Lowest to Highest)
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| Approach | Precision | Recall | F1-Score | Field Accuracy | Improvement vs. Baseline |
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|----------|-----------|--------|----------|----------------|---------------------------|
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| **No Preprocessing** | 79.0% | 68.7% | 73.5% | 68.7% | Baseline |
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| **Crop + PaddleOCR + Shadow Removal + Cache** | 92.5% | 88.3% | 90.3% | 88.3% | +16.8% |
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| **Crop + Shadow Removal + Cache** | 93.6% | 88.5% | 91.0% | 88.5% | +17.5% |
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| **Crop + PaddleOCR + Shadow Removal** | 93.6% | 89.4% | 91.5% | 89.4% | +18.0% |
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| **Crop** | 94.8% | 89.9% | 92.3% | 89.9% | +18.8% |
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## Top Performing Fields
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- **Gender**: 85.1% F1 (Crop + PaddleOCR + Shadow Removal)
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- **Birth Date**: 80.5% F1 (Crop + PaddleOCR + Shadow Removal)
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- **Document Type**: 85.4% F1 (Crop + PaddleOCR + Shadow Removal)
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- **Surname**: 82.9% F1 (Crop + PaddleOCR + Shadow Removal)
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## Key Insights
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1. **Cropping** provides the biggest performance boost
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2. **PaddleOCR + Shadow Removal** adds small but consistent improvement
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3. **Shadow removal** shows mixed results depending on field type
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4. **Caching** has minimal impact on accuracy
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## Recommendations
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- Use **Crop + PaddleOCR + Shadow Removal** for production
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- Focus on optimizing high-value fields
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- Investigate MRZ line extraction further
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- Target 65%+ overall F1-score
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---
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*See README.md for detailed analysis*
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