metadata
license: cc-by-nc-nd-4.0
pipeline_tag: object-detection
tags:
- yolo11
- ultralytics
- yolo
- object-detection
- pytorch
- cs2
- Counter Strike
Counter Strike 2 players detector
Supported Labels
[ 'c', 'ch', 't', 'th' ]
All models in this series
- yolo11n_cs2 (~6mb)
- yolo11s_cs2 (~18mb)
- yolo11m_cs2 (~39mb)
- yolo11l_cs2 (~49mb)
- yolo11x_cs2 (~109mb)
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)
- yolo11x_cs2_fp16.engine (384x640 5 ts, 5 ths, 7.0ms)
- yolo11x_cs2.engine (384x640 5 ts, 5 ths, 15.5ms)
- yolo11x_cs2_fp16.onnx (640x640 5 ts, 5 ths, 48.7ms)
- yolo11x_cs2.onnx (384x640 5 ts, 5 ths, 178.8ms)
- yolo11x_cs2.pt (384x640 5 ts, 5 ths, 62.2ms)
Dataset info
Data from over 127 games, where the footage has been tagged in detail.
Train info
The training took place over 150 epochs.
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