![keremberke/yolov8n-shoe-classification](https://huggingface.co/keremberke/yolov8n-shoe-classification/resolve/main/thumbnail.jpg)
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
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Dataset used to train keremberke/yolov8n-shoe-classification
Evaluation results
- top1 accuracy on shoe-classificationvalidation set self-reported0.687
- top5 accuracy on shoe-classificationvalidation set self-reported1.000