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Diagram Detr R50 Finetuned
This model is an object detection model based on the DETR architecture, fine-tuned on the bpmn-shapes dataset, suitable for detecting elements in diagrams.
Downloads 26
Release Time : 1/19/2024
Model Overview
A vision-based object detection model using the DETR architecture, specifically optimized for detecting shape elements in BPMN diagrams.
Model Features
Transformer-based detection architecture
Utilizes the DETR architecture, combining the strengths of Transformer and CNN for end-to-end object detection.
Optimized for diagram elements
Fine-tuned specifically on the bpmn-shapes dataset, making it ideal for detecting various shape elements in diagrams.
Efficient training process
Uses mixed-precision training and a linear learning rate scheduler to optimize training efficiency.
Model Capabilities
Diagram element detection
Object localization
Shape recognition
Use Cases
Business process modeling
BPMN diagram analysis
Automatically detects and identifies various process elements in BPMN diagrams.
Validation loss 0.9817
Document processing
Technical document parsing
Extracts diagrams and graphical elements from technical documents.
PyTorch
Safetensors
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