jparedesDS/valorant-yolo11m

Valorant Players Detector

Supported Labels

['Body', 'Head']

ALL my models YOLOv10 & YOLOv9

• Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c
• Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s
• Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m
• Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b
• Yolov10b: https://huggingface.co/jparedesDS/valorant-yolov10b

How to use

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolov10b_vlr.pt')

# Run inference on 'image.png' with arguments
model.predict(
    'image.png',
    save=True,
    device=0
    )

Confusion matrix normalized

Labels

Results

Predict

YOLO11m summary (fused): 303 layers, 20,031,574 parameters, 0 gradients, 67.7 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 11/11 [00:06<00:00,  1.71it/s]
                   all        999       2016      0.963      0.898      0.931      0.655
                  Body        966       1029      0.971      0.935      0.958      0.791
                  Head        936        987      0.955      0.862      0.904      0.519

Others models Counter Strike 2 YOLOv10m Object Detection

https://huggingface.co/jparedesDS/valorant-yolov10b