anydoclayout

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 / _ \ | '_ \| | | | | | |/ _ \ / __| | / _` | | | |/ _ \| | | | __|
 / ___ \| | | | |_| | |_| | (_) | (__| |__| (_| | |_| | (_) | |_| | |_
/_/ \_\_| |_|\__, |____/ \___/ \___|_____\__,_|\__, |\___/ \__,_|\__|
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train datasets

1. labels info

{0: 'header',
 1: 'title',
 2: 'text',
 3: 'table',
 4: 'figure',
 5: 'formula',
 6: 'footer',
 7: 'pagenum'}

2. datasets info

3. eval results

Class Images Instances Box(P R)
 all 5500 52274 0.921 0.897
header 1461 2337 0.92 0.878
 title 2308 5473 0.896 0.893 
 text 4149 34156 0.937 0.927
 table 1476 1913 0.946 0.958
figure 1842 3343 0.94 0.94
formula 735 1506 0.881 0.876
footer 745 1157 0.909 0.781
pagenum 2164 2389 0.938 0.919

if you want to get datasets

how to use

from pathlib import Path
from ultralytics import YOLO
modelfile = Path(model_dir).joinpath('anydoclayout-yolo11s-imgsz1280.pt')
model = YOLO(modelfile)
res = model.predict('your img file', imgsz = 1280)

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