metadata
license: cc-by-nc-nd-4.0
pipeline_tag: object-detection
tags:
- yolov10
- ultralytics
- yolo
- object-detection
- pytorch
- cs2
- Counter Strike
Counter Strike 2 players detector
Supported Labels
[ 'c', 'ch', 't', 'th' ]
All models in this series
- yoloV10n_cs2 (5.5mb)
- yoloV10s_cs2 (15.7mb)
- yoloV10m_cs2 (31.9mb)
- yoloV10b_cs2 (39.7mb)
- yoloV10l_cs2 (50.0mb)
- yoloV10x_cs2 (61.4mb)
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)
- yolov10s_cs2_fp16.engine (640x640 5 ts, 6 ths, 3.0ms)
- yolov10s_cs2.engine (640x640 5 ts, 6 ths, 4.5ms)
- yolov10s_cs2_fp16.onnx (640x640 5 ts, 6 ths, 80.4ms)
- yolov10s_cs2.onnx (640x640 5 ts, 6 ths, 76.6ms)
- yolov10s_cs2.pt (384x640 5 ts, 5 ths, 86.7ms)
Dataset info
Data from over 120 games, where the footage has been tagged in detail.
Train info
The training took place over 150 epochs.
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