Modelpublic

chanelcolgate/valorant-object-detection

sourceHugging Faceupdated 3y agoView on Hugging Face

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Model Card

tags:

—ultralyticsplus
—yolov8
—ultralytics
—yolo
—vision
—object-detection
—pytorch

libraryname: ultralytics libraryversion: 8.0.239 inference: false

model-index:

—name: chanelcolgate/valorant-object-detection results:
—task: type: object-detection

metrics:

—type: precision # since mAP@0.5 is not available on hf.co/metrics value: 0.95137 # min: 0.0 - max: 1.0 name: mAP@0.5(box) ---

Supported Labels

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

How to use

—Install ultralyticsplus:

bash

pip install ultralyticsplus==0.0.29 ultralytics==8.0.239

—Load model and perform prediction:

python

from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('chanelcolgate/valorant-object-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()