readme:  
  ---
  tags:
  - ultralyticsplus
  - yolov8
  - ultralytics
  - yolo
  - vision
  - object-detection
  - pytorch
  
  library_name: ultralytics
  library_version: 8.0.21
  inference: false
  
  model-index:
  - name: uisikdag/msgsulogo_v8
    results:
    - task:
        type: object-detection
  
      metrics:
        - type: precision  # since mAP@0.5 is not available on hf.co/metrics
          value: 0.88786  # min: 0.0 - max: 1.0
          name: mAP@0.5(box)
  ---
  
  <div align="center">
    <img width="640" alt="uisikdag/msgsulogo_v8" src="https://huggingface.co/uisikdag/msgsulogo_v8/resolve/main/thumbnail.jpg">
  </div>
  
  ### Supported Labels
  
  ```
  ['msgsu']
  ```
  
  ### 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, render_result
  
  # load model
  model = YOLO('uisikdag/msgsulogo_v8')
  
  # set model parameters
  model.overrides['conf'] = 0.25  # NMS confidence threshold
  model.overrides['iou'] = 0.45  # NMS IoU threshold
  model.overrides['agnostic_nms'] = False  # NMS class-agnostic
  model.overrides['max_det'] = 1000  # maximum number of detections per image
  
  # 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].boxes)
  render = render_result(model=model, image=image, result=results[0])
  render.show()
  ```
  
  