metadata
language:
- en
- es
base_model:
- jparedesDS/valorant-yolov10b
pipeline_tag: object-detection
tags:
- valorant
- yolov10
- aimbot
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
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
YOLOv10b summary (fused): 383 layers, 20,414,236 parameters, 0 gradients, 97.9 GFLOPs
Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 36/36 [00:06<00:00, 5.30it/s]
all 999 2016 0.959 0.886 0.925 0.631
Body 966 1029 0.969 0.914 0.955 0.76
Head 936 987 0.948 0.857 0.896 0.503