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-yolov8n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AvoCahDoe/invoice-layout-yolov8n with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("AvoCahDoe/invoice-layout-yolov8n") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
File size: 271 Bytes
f0e98c4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | path: E:/invoice-extractor/training_model/data/yolo_annotated
train: images/train
val: images/val
test: images/test
names:
0: invoice_metadata
1: vendor_block
2: customer_block
3: table_block
4: line_item
5: summary_block
6: payment_block
7: Column
nc: 8
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