Object Detection
TensorBoard
PyTorch
English
ultralytics
v8
ultralyticsplus
yolov8
yolo
vision
table detection
table extraction
table classification
document analysis
unstructured document
unstructured table extraction
structured table extraction
unstructured table detection
structured table detection
Eval Results
metadata
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
library_name: ultralytics
library_version: 8.0.43
inference: false
model-index:
- name: foduucom/table-detection-and-extraction
results:
- task:
type: object-detection
metrics:
- type: precision
value: 0.96196
name: [email protected](box)
Supported Labels
['bordered', 'borderless']
How to use
- Install ultralyticsplus:
pip install ultralyticsplus==0.0.28 ultralytics==8.0.43
- Load model and perform prediction:
from ultralyticsplus import YOLO, render_result
# load model
model = YOLO('foduucom/table-detection-and-extraction')
# set model parameters
model.overrides['conf'] = 0.25 # NMS confidence threshold
model.overrides['iou'] = 0.45 # NMS IoU threshold
model.overrides['agnostic_nms'] = False # NMS class-agnostic
model.overrides['max_det'] = 1000 # maximum number of detections per image
# set image
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'
# perform inference
results = model.predict(image)
# observe results
print(results[0].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()