metadata
license: cc-by-nc-nd-4.0
pipeline_tag: object-detection
tags:
- yolov9
- ultralytics
- yolo
- object-detection
- pytorch
- cs2
- Counter Strike
Counter Strike 2 players detector
Supported Labels
[ 'c', 'ch', 't', 'th' ]
All models
- yoloV8n_cs2 (6mb)
- yoloV8s_cs2 (21mb)
- yoloV9c_cs2 (50mb)
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 YOLOv8.2.3 🚀 Python-3.10.11 torch-2.0.1+cu118 CUDA:0 (NVIDIA GeForce RTX 4060, 8187MiB):
- yolov9c_cs2_fp16.engine (640x640 5 ts, 5 ths, 5.0ms)
- yolov9c_cs2.engine (640x640 5 ts, 5 ths, 15.1ms)
- yolov9c_cs2.onnx (640x640 5 ts, 5 ths, 27.5ms)
- yolov9c_cs2.pt (384x640 5 ts, 5 ths, 272.8ms)
Dataset info
Data from over 70 games, where the footage has been tagged in detail.
Train info
The training took place over 100 epochs.
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