支持的标签

['adidas', 'converse', 'nike']

如何使用

• 安装 ultralyticsplus :

pip install ultralyticsplus==0.0.24 ultralytics==8.0.23

• 加载模型并进行预测:

from ultralyticsplus import YOLO, postprocess_classify_output

# load model
model = YOLO('keremberke/yolov8m-shoe-classification')

# set model parameters
model.overrides['conf'] = 0.25  # model confidence threshold

# 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].probs) # [0.1, 0.2, 0.3, 0.4]
processed_result = postprocess_classify_output(model, result=results[0])
print(processed_result) # {"cat": 0.4, "dog": 0.6}

更多模型可在此处获取: awesome-yolov8-models