# 🖼️ Saint George on a Bike – Mask R-CNN for Iconographic Object Detection
## Model Summary
This model uses the [Matterport Mask R-CNN](https://github.com/matterport/Mask_RCNN) implementation fine-tuned for detecting iconographic and symbolic elements in religious artworks. It is developed as part of the **Saint George on a Bike** project to enable semantic enrichment and understanding of historical imagery.
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## 🧠 Model Details
- **Architecture**: Mask R-CNN with ResNet backbone
- **Framework**: TensorFlow 1.14.0 + Keras 2.2.5
- **Source**: https://github.com/matterport/Mask_RCNN
- **Configuration**:
- `NUM_CLASSES`: 69+1 (background)
- `DETECTION_MIN_CONFIDENCE`: 0.76
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## 🎯 Use Cases
- Iconography detection in religious paintings
- Digital humanities and art historical research
- Training multimodal models for cultural heritage
- Enriching metadata in museum and archive collections
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## 🏷️ Labels (Selected)
The model detects over 40 iconographic concepts inc…
# 🖼️ Saint George on a Bike – Mask R-CNN for Iconographic Object Detection
## Model Summary
This model uses the [Matterport Mask R-CNN](https://github.com/matterport/Mask_RCNN) implementation fine-tuned for detecting iconographic and symbolic elements in religious artworks. It is developed as part of the **Saint George on a Bike** project to enable semantic enrichment and understanding of historical imagery.
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## 🧠 Model Details
- **Architecture**: Mask R-CNN with ResNet backbone
- **Framework**: TensorFlow 1.14.0 + Keras 2.2.5
- **Source**: https://github.com/matterport/Mask_RCNN
- **Configuration**:
- `NUM_CLASSES`: 69+1 (background)
- `DETECTION_MIN_CONFIDENCE`: 0.76
---
## 🎯 Use Cases
- Iconography detection in religious paintings
- Digital humanities and art historical research
- Training multimodal models for cultural heritage
- Enriching metadata in museum and archive collections
<img src="cruc.png" alt="Example of usage" width="200"/>
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## 🏷️ Labels (Selec…
