
<div align="center">
  <img width="640" alt="keremberke/yolov8n-valorant-detection" src="https://huggingface.co/keremberke/yolov8n-valorant-detection/resolve/main/thumbnail.jpg">
</div>

### Supported Labels

```
['dropped spike', 'enemy', 'planted spike', 'teammate']
```

### 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('keremberke/yolov8n-valorant-detection')

# 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()
```

**More models available at: [awesome-yolov8-models](https://yolov8.xyz)**
{"library_name": "ultralytics", "tags": ["ultralyticsplus", "yolov8", "ultralytics", "yolo", "vision", "object-detection", "pytorch", "awesome-yolov8-models"], "datasets": ["keremberke/valorant-object-detection"], "library_version": "8.0.21", "inference": false, "model-index": [{"name": "keremberke/yolov8n-valorant-detection", "results": [{"task": {"type": "object-detection"}, "dataset": {"name": "valorant-object-detection", "type": "keremberke/valorant-object-detection", "split": "validation"}, "metrics": [{"type": "precision", "value": 0.93688, "name": "mAP@0.5(box)"}]}]}]}
ultralytics tensorboard v8 ultralyticsplus yolov8 yolo vision object-detection pytorch awesome-yolov8-models dataset:keremberke/valorant-object-detection model-index region:us
TAGS
#ultralytics #tensorboard #v8 #ultralyticsplus #yolov8 #yolo #vision #object-detection #pytorch #awesome-yolov8-models #dataset-keremberke/valorant-object-detection #model-index #region-us 


<div align="center">
  <img width="640" alt="keremberke/yolov8n-valorant-detection" src="URL
</div>

### Supported Labels



### How to use

- Install ultralyticsplus:



- Load model and perform prediction:



More models available at: awesome-yolov8-models
### Supported Labels ### How to use

- Install ultralyticsplus:



- Load model and perform prediction:



More models available at: awesome-yolov8-models
TAGS
#ultralytics #tensorboard #v8 #ultralyticsplus #yolov8 #yolo #vision #object-detection #pytorch #awesome-yolov8-models #dataset-keremberke/valorant-object-detection #model-index #region-us 
 ### Supported Labels ### How to use

- Install ultralyticsplus:



- Load model and perform prediction:



More models available at: awesome-yolov8-models
TAGS
#ultralytics #tensorboard #v8 #ultralyticsplus #yolov8 #yolo #vision #object-detection #pytorch #awesome-yolov8-models #dataset-keremberke/valorant-object-detection #model-index #region-us 
### Supported Labels### How to use

- Install ultralyticsplus:



- Load model and perform prediction:



More models available at: awesome-yolov8-models