--- tags: - ultralyticsplus - yolov8 - ultralytics - yolo - vision - image-classification - pytorch library_name: ultralytics library_version: 8.0.239 inference: false model-index: - name: feliperafael/my_yolo_model_pantene results: - task: type: image-classification metrics: - type: accuracy value: 0.8 # min: 0.0 - max: 1.0 name: top1 accuracy - type: accuracy value: 1 # min: 0.0 - max: 1.0 name: top5 accuracy ---
feliperafael/my_yolo_model_pantene
### Supported Labels ``` ['downy', 'pantene'] ``` ### How to use - Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus): ```bash pip install ultralyticsplus==0.0.29 ultralytics==8.0.239 ``` - Load model and perform prediction: ```python from ultralyticsplus import YOLO, postprocess_classify_output # load model model = YOLO('feliperafael/my_yolo_model_pantene') # 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} ```