tags: | |
- ultralyticsplus | |
- yolov8 | |
- ultralytics | |
- yolo | |
- vision | |
- object-detection | |
- pytorch | |
- awesome-yolov8-models | |
library_name: ultralytics | |
library_version: 8.0.21 | |
inference: false | |
datasets: | |
- keremberke/table-extraction | |
model-index: | |
- name: keremberke/yolov8m-table-extraction | |
results: | |
- task: | |
type: object-detection | |
dataset: | |
type: keremberke/table-extraction | |
name: table-extraction | |
split: validation | |
metrics: | |
- type: precision | |
value: 0.95194 | |
name: mAP@0.5(box) | |
license: agpl-3.0 | |
<div align="center"> | |
<img width="640" alt="keremberke/yolov8m-table-extraction" src="https://huggingface.co/keremberke/yolov8m-table-extraction/resolve/main/thumbnail.jpg"> | |
</div> | |
### Supported Labels | |
``` | |
['bordered', 'borderless'] | |
``` | |
### How to use | |
- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): | |
```bash | |
pip install ultralyticsplus==0.0.23 ultralytics==8.0.21 | |
``` | |
- Load model and perform prediction: | |
```python | |
from ultralyticsplus import YOLO, render_result | |
# load model | |
model = YOLO('keremberke/yolov8m-table-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() | |
``` | |
**More models available at: [awesome-yolov8-models](https://yolov8.xyz)** |