keremberke

/

yolov8n-shoe-classification

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Supported Labels

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

How to use

• Install ultralyticsplus:

pip install ultralyticsplus==0.0.24 ultralytics==8.0.23

• Load model and perform prediction:

from ultralyticsplus import YOLO, postprocess_classify_output

# load model
model = YOLO('keremberke/yolov8n-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}

More models available at: awesome-yolov8-models