Object Detection
ultralytics
English
German
yolo
yolo11
invoice
document-layout
document-understanding
ocr-prep
invoice-extraction
Eval Results (legacy)
Instructions to use AvoCahDoe/invoice-layout-yolo11m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AvoCahDoe/invoice-layout-yolo11m with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("AvoCahDoe/invoice-layout-yolo11m") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Invoice Layout YOLO — Model Comparison
Ranked by test mAP50
| Rank | Model | test mAP50 | test mAP50-95 | val mAP50 | Precision | Recall |
|---|---|---|---|---|---|---|
| 1 | yolov8n | 0.9600 | 0.7167 | 0.8824 | 0.9502 | 0.9592 |
| 2 | yolov8s | 0.9006 | 0.6739 | 0.8580 | 0.9419 | 0.8677 |
| 3 | yolov8x | 0.8757 | 0.6224 | 0.8798 | 0.9144 | 0.8735 |
| 4 | yolo11x | 0.8738 | 0.6127 | 0.8944 | 0.9484 | 0.8530 |
| 5 | yolo11m | 0.8418 | 0.4926 | 0.8824 | 0.9033 | 0.8466 |
| 6 | yolov8m | 0.8388 | 0.5289 | 0.8646 | 0.9077 | 0.8580 |
Per-model run directories
- yolov8n:
E:\invoice-extractor\training_model\runs\comparison\yolov8n - yolov8s:
E:\invoice-extractor\training_model\runs\comparison\yolov8s - yolov8m:
E:\invoice-extractor\training_model\runs\comparison\yolov8m - yolo11m:
E:\invoice-extractor\training_model\runs\comparison\yolo11m - yolov8x:
E:\invoice-extractor\training_model\runs\comparison\yolov8x - yolo11x:
E:\invoice-extractor\training_model\runs\comparison\yolo11x