Edit model card

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\yolov**_cs2.pt')

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

Predict info

Ultralytics YOLOv8.2.90 🚀 Python-3.12.5 torch-2.3.1+cu121 CUDA:0 (NVIDIA GeForce RTX 4060, 8188MiB)

  • yolov10b_cs2_fp16.engine (640x640 5 ts, 5 ths, 7.1ms)
  • yolov10b_cs2.engine (640x640 5 ts, 5 ths, 11.2ms)
  • yolov10b_cs2_fp16.onnx (640x640 5 ts, 5 ths, 246.2ms)
  • yolov10b_cs2.onnx (640x640 5 ts, 5 ths, 257.6ms)
  • yolov10b_cs2.pt (384x640 5 ts, 5 ths, 114.4ms)

Dataset info

Data from over 120 games, where the footage has been tagged in detail.

image/jpg image/jpg

Train info

The training took place over 150 epochs.

image/png

You can also support me with a cup of coffee: donate

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Examples
Inference API (serverless) does not yet support yolov10 models for this pipeline type.

Collection including Vombit/yolov10b_cs2