metadata
tags:
- yolo11
- valorant
- object
- detection
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