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chanelcolgate/cadivi-segment-yolov8m-v2
cadivi-segment-yolov8m-v2 is a image segmentation model from chanelcolgate. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for ultralytics.
<div align="center" <img width="640" alt="chanelcolgate/cadivi-segment-yolov8m-v2" src="https://huggingface.co/chanelcolgate/cadivi-segment-yolov8m-v2/resolve/main/thumbnail.jpg" </div
Downloads · 30 days
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.pt54.8 MB · 98%
From the Hugging Face model README
['cable']
pip install ultralyticsplus==0.1.0 ultralytics==8.0.239
from ultralyticsplus import YOLO, render_result
# load model
model = YOLO('chanelcolgate/cadivi-segment-yolov8m-v2')
# 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)
print(results[0].masks)
render = render_result(model=model, image=image, result=results[0])
render.show()