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--- |
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tags: |
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- ultralyticsplus |
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- yolov8 |
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- ultralytics |
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- yolo |
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- vision |
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- image-classification |
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- pytorch |
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- awesome-yolov8-models |
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library_name: ultralytics |
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library_version: 8.0.23 |
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inference: false |
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datasets: |
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- keremberke/shoe-classification |
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model-index: |
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- name: keremberke/yolov8s-shoe-classification |
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results: |
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- task: |
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type: image-classification |
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dataset: |
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type: keremberke/shoe-classification |
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name: shoe-classification |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 0.68675 |
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name: top1 accuracy |
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- type: accuracy |
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value: 1 |
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name: top5 accuracy |
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--- |
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<div align="center"> |
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<img width="640" alt="keremberke/yolov8s-shoe-classification" src="https://huggingface.co/keremberke/yolov8s-shoe-classification/resolve/main/thumbnail.jpg"> |
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</div> |
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### Supported Labels |
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``` |
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['adidas', 'converse', 'nike'] |
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``` |
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### How to use |
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- Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): |
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```bash |
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pip install ultralyticsplus==0.0.24 ultralytics==8.0.23 |
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``` |
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- Load model and perform prediction: |
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```python |
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from ultralyticsplus import YOLO, postprocess_classify_output |
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# load model |
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model = YOLO('keremberke/yolov8s-shoe-classification') |
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# set model parameters |
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model.overrides['conf'] = 0.25 # model confidence threshold |
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# set image |
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image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg' |
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# perform inference |
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results = model.predict(image) |
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# observe results |
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print(results[0].probs) # [0.1, 0.2, 0.3, 0.4] |
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processed_result = postprocess_classify_output(model, result=results[0]) |
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print(processed_result) # {"cat": 0.4, "dog": 0.6} |
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``` |
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**More models available at: [awesome-yolov8-models](https://yolov8.xyz)** |
