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-yolov8m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use AvoCahDoe/invoice-layout-yolov8m with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("AvoCahDoe/invoice-layout-yolov8m") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9b468054f9c0fdb3a8ab3f33654a7971578d8f8de7f6b5f4d6975226dcdc376
- Size of remote file:
- 52.1 MB
- SHA256:
- 43061dbfc67fd0eb867f65f95395404da83b09995cce37750dd7f0b4b1c1589c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.