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Vombit
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yolo11s_cs2

Object Detection
ultralytics
ONNX
PyTorch
yolo11
yolo
cs2
Counter Strike
Model card Files
xet
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Counter Strike 2 players detector

Supported Labels 

[ 'c', 'ch', 't', 'th' ]

All models in this series

How to use 

# load Yolo
from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolo**_cs2.pt')

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

Predict info

Ultralytics 8.3.68 🚀 Python-3.11.0 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4060, 8187MiB)

  • yolo11s_cs2_fp16.engine (384x640 5 ts, 5 ths, 3.8ms)
  • yolo11s_cs2.engine (384x640 5 ts, 5 ths, 5.0ms)
  • yolo11s_cs2_fp16.onnx (640x640 5 ts, 5 ths, 13.0ms)
  • yolo11s_cs2.onnx (384x640 5 ts, 5 ths, 94.7ms)
  • yolo11s_cs2.pt (384x640 5 ts, 5 ths, 58.9ms)

Dataset info

Data from over 127 games, where the footage has been tagged in detail.

image/jpg image/jpg

Train info

The training took place over 150 epochs.

image/png

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