
Supported Labels
['tennis ball']
How to use
- Install ultralyticsplus:
pip install ultralyticsplus==0.1.0 ultralytics==8.0.239
- Load model and perform prediction:
from ultralyticsplus import YOLO, render_result
# load model
model = YOLO('chanelcolgate/tennis-analysis-v1')
# 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()
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Inference Providers
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This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model authors have turned it off explicitly.
Dataset used to train chanelcolgate/tennis-analysis-v1
Evaluation results
- mAP@0.5(box) on yenthienvietvalidation set self-reported0.867