Object Detection
ultralytics
English
German
yolo
yolov8
invoice
document-layout
document-understanding
ocr-prep
invoice-extraction
Eval Results (legacy)
Instructions to use AvoCahDoe/invoice-layout-yolov8x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AvoCahDoe/invoice-layout-yolov8x with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("AvoCahDoe/invoice-layout-yolov8x") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Link Hub collection in model card
Browse files
README.md
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Fine-tuned **YOLOv8x** for **8-class invoice document layout** region detection (metadata, vendor/customer blocks, table, line items, summary, payment, column headers).
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| **Architecture** | YOLOv8x (68.2M params, 257.8 GFLOPs) |
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Fine-tuned **YOLOv8x** for **8-class invoice document layout** region detection (metadata, vendor/customer blocks, table, line items, summary, payment, column headers).
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Part of the Hub collection **[Invoice Layout Extraction](https://huggingface.co/collections/AvoCahDoe/invoice-layout-extraction-6a39cd2a061a508c8049d825)**.
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| **Architecture** | YOLOv8x (68.2M params, 257.8 GFLOPs) |
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