Object Detection
ultralytics
yolo
yolo11
blueprint
floorplan
architecture
construction
document-layout
cad
Instructions to use GreenMap/yolo11x-blueprint-layout-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use GreenMap/yolo11x-blueprint-layout-detector with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("GreenMap/yolo11x-blueprint-layout-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
GreenMap/yolo11x-blueprint-layout-detector
Overview
YOLO11x model trained to detect the main layout elements on architectural and construction blueprints.
- Detects the main drawing area.
- Detects legend blocks.
- Detects title blocks.
- Trained on architectural floor plans and construction drawings.
Classes
| ID | Class | Purpose |
|---|---|---|
| 0 | drawing_area | Main drawing area. |
| 1 | legend_block | Legend with symbols and hatch patterns. |
| 2 | title_block | Drawing title block and metadata. |
Training Metrics
Validation Metrics
| Class | Images | Instances | Precision | Recall | mAP50 | mAP50-95 |
|---|---|---|---|---|---|---|
| all | 60 | 313 | 0.927 | 0.932 | 0.955 | 0.874 |
| drawing_area | 59 | 218 | 0.927 | 0.936 | 0.976 | 0.813 |
| legend_block | 34 | 36 | 0.859 | 0.861 | 0.893 | 0.837 |
| title_block | 59 | 59 | 0.995 | 1.000 | 0.995 | 0.972 |
Training
- Base model: YOLO11x
- Task: Object Detection
- Classes: drawing_area, legend_block, title_block
- Input size: 1472 × 1472
- Framework: Ultralytics YOLO
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