DocType - Document Image Classification

A high-performance MobileNetV3-based document classifier that categorizes document images into 7 distinct types. Optimized for production deployment with ONNX format.

🎯 Model Overview

This model classifies document images into the following categories:

Category	Description
chart	Charts, graphs, and data visualizations
diagram	Flowcharts, diagrams, and technical drawings
document_handwritten	Handwritten documents and notes
document_printed	Printed text documents
map	Maps and geographic visualizations
photo	Photographs and natural images
screenshot	Screenshots and screen captures

🚀 Performance

Model Metrics

• Architecture: MobileNetV3-Large (transfer learning + fine-tuning)
• Input Size: 320×320 pixels
• Parameters: ~5.4M (lightweight and efficient)
• Inference Time: ~10-30ms on CPU (depending on hardware)

Training Details

• Dataset Size: 21,000 images (17,500 train / 2,100 val / 1,400 test)
• Training Strategy:
  • Phase 1: Transfer learning with frozen base (40 epochs)
  • Phase 2: Fine-tuning entire model (20 epochs)
• Data Augmentation: Rotation, shifts, zoom, brightness variation
• Optimizer: Adam (lr=0.001 → 1e-5 for fine-tuning)

📮 Citation

If you use this model in your research or project, please cite.