Vombit/yolov8s_cs2
作者 Vombit | 下载 17 | 点赞 2 | 更新 2026-01-21
这个仓库里有什么
- 2 个 ONNX 模型(.onnx 文件)
- 9 个文件,其中 .engine 2 个、.onnx 2 个、.md 1 个、.jpg 1 个、.png 1 个、.pt 1 个
- 最近更新:2026-01-21
ONNX 文件清单
怎么用
这些 ONNX 文件可以直接用 ONNX Runtime 加载运行;想先看网络结构,可以把文件上传到 Netron 在线查看器 查看。下载链接指向 Hugging Face 原始文件。
说明文档
Counter Strike 2 players detector
Supported Labels
[ 'c', 'ch', 't', 'th' ]
All models
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):
- yolov8s_cs2_fp16.engine (640x640 5 ts, 5 ths, 3.0ms)
- yolov8s_cs2.engine (640x640 5 ts, 5 ths, 5.0ms)
- yolov8s_cs2.onnx (640x640 5 ts, 5 ths, 31.0ms)
- yolov8s_cs2.pt (384x640 5 ts, 5 ths, 218.1ms)
Dataset info
Data from over 70 games, where the footage has been tagged in detail. <img width="640" src="https://huggingface.co/Vombit/yolov8s_cs2/resolve/main/labels.jpg">
Train info
The training took place over 100 epochs. <img width="640" src="https://huggingface.co/Vombit/yolov8s_cs2/resolve/main/results.png">
模型信息
object-detection
ultralytics
ultralytics
onnx
yolov8
yolo
object-detection
pytorch
cs2
Counter Strike
license:cc-by-nc-nd-4.0
region:us
↓ 17
♥ 2
创建时间: 2024-04-27
更新时间: 2026-01-21
在 Hugging Face 上查看文件 (9)
.gitattributes
README.md
labels.jpg
results.png
yolov8s_cs2.engine
yolov8s_cs2.onnx
ONNX
yolov8s_cs2.pt
yolov8s_cs2_fp16.engine
yolov8s_cs2_fp16.onnx
ONNX