readme:  
  ---
  tags:
  - ultralyticsplus
  - yolov8
  - ultralytics
  - yolo
  - vision
  - image-classification
  - pytorch
  
  library_name: ultralytics
  library_version: 8.0.21
  inference: false
  
  model-index:
  - name: uisikdag/fogsmog_v8
    results:
    - task:
        type: image-classification
  
      metrics:
        - type: accuracy
          value: 0.8375  # min: 0.0 - max: 1.0
          name: top1 accuracy
        - type: accuracy
          value: 1  # min: 0.0 - max: 1.0
          name: top5 accuracy
  ---
  
  <div align="center">
    <img width="640" alt="uisikdag/fogsmog_v8" src="https://huggingface.co/uisikdag/fogsmog_v8/resolve/main/thumbnail.jpg">
  </div>
  
  ### Supported Labels
  
  ```
  ['fog', 'smog']
  ```
  
  ### How to use
  
  - Install [ultralyticsplus](https://github.com/fcakyon/ultralyticsplus):
  
  ```bash
  pip install ultralyticsplus==0.0.23 ultralytics==8.0.21
  ```
  
  - Load model and perform prediction:
  
  ```python
  from ultralyticsplus import YOLO, postprocess_classify_output
  
  # load model
  model = YOLO('uisikdag/fogsmog_v8')
  
  # 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}
  ```
  
  