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--- |
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license: mit |
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pipeline_tag: image-classification |
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datasets: |
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- monkt/doctype |
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--- |
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# DocType - Document Image Classification |
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A high-performance MobileNetV3-based document classifier that categorizes document images into 7 distinct types. Optimized for production deployment with ONNX format. |
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## 🎯 Model Overview |
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This model classifies document images into the following categories: |
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| Category | Description | |
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|----------|-------------| |
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| **chart** | Charts, graphs, and data visualizations | |
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| **diagram** | Flowcharts, diagrams, and technical drawings | |
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| **document_handwritten** | Handwritten documents and notes | |
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| **document_printed** | Printed text documents | |
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| **map** | Maps and geographic visualizations | |
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| **photo** | Photographs and natural images | |
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| **screenshot** | Screenshots and screen captures | |
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## 🚀 Performance |
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### Model Metrics |
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- **Architecture**: MobileNetV3-Large (transfer learning + fine-tuning) |
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- **Input Size**: 320×320 pixels |
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- **Parameters**: ~5.4M (lightweight and efficient) |
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- **Inference Time**: ~10-30ms on CPU (depending on hardware) |
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### Training Details |
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- **Dataset Size**: 21,000 images (17,500 train / 2,100 val / 1,400 test) |
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- **Training Strategy**: |
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- Phase 1: Transfer learning with frozen base (40 epochs) |
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- Phase 2: Fine-tuning entire model (20 epochs) |
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- **Data Augmentation**: Rotation, shifts, zoom, brightness variation |
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- **Optimizer**: Adam (lr=0.001 → 1e-5 for fine-tuning) |
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## 📮 Citation |
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If you use this model in your research or project, please cite. |
