YOLOv10-Document-Layout-Analysis
| Property | Value |
|---|---|
| License | AGPL-3.0 |
| Dataset | DocLayNet |
| Best Performance | 92.4% mAP50 (YOLOv10-x) |
| Paper | DocLayNet Paper |
What is YOLOv10-Document-Layout-Analysis?
This is a state-of-the-art document layout analysis model that leverages the powerful YOLOv10 architecture to detect and analyze document structures. The model was trained on the extensive DocLayNet dataset, comprising 69,103 training images, 6,480 validation images, and 4,994 test images, using 4 A100 GPUs.
Implementation Details
The model comes in six variants (nano to extra-large), offering different trade-offs between performance and computational requirements. The YOLOv10-x variant achieves the best performance with 92.4% mAP50 and 74.0% mAP50-95.
- Multiple model sizes available: x, b, l, m, s, n
- Trained on DocLayNet-base dataset
- Optimized for real-time document layout detection
Core Capabilities
- High-accuracy document layout detection
- Real-time performance capabilities
- Robust across different document types
- Flexible deployment options with various model sizes
Frequently Asked Questions
Q: What makes this model unique?
This model combines the latest YOLOv10 architecture with comprehensive document layout analysis capabilities, achieving state-of-the-art performance (92.4% mAP50) while maintaining real-time processing capabilities.
Q: What are the recommended use cases?
The model is ideal for document processing systems, automated document analysis, content extraction, and document digitization workflows where accurate layout analysis is crucial.
