README.md

metadata

language:
  - en
  - es
base_model:
  - jameslahm/yolov10s
tags:
  - GAMES
  - COUNTER STRIKE2
  - CS2
  - VIDEOGAMES
  - CS
  - OBJECT DETECTION
  - YOLO
  - YOLOV10
  - YOLOV10S
pipeline_tag: object-detection

Counter Strike 2 players detector

Supported Labels

['CT', 'CT_head', 'T', 'T_head']

ALL my models YOLOv10 & YOLOv9

• Yolov10s: https://huggingface.co./jparedesDS/cs2-yolov10s
• Yolov9c: https://huggingface.co./jparedesDS/cs2-yolov9c
• Yolov10m: https://huggingface.co./jparedesDS/cs2-yolov10m
• Yolov10b: https://huggingface.co./jparedesDS/cs2-yolov10b

How to use

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolov10s_cs2.pt')

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

Labels

Results

Predict

YOLOv10s summary (fused): 293 layers, 8,038,056 parameters, 0 gradients, 24.5 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 5/5 [00:03<00:00,  1.41it/s]
                   all        160        372      0.958       0.94      0.979      0.772
               ct_body         88        110      0.964      0.964      0.988      0.861
               ct_head         82        104      0.946      0.847      0.953      0.634
                t_body         70         84      0.986      0.976       0.99      0.866
                t_head         62         74      0.938      0.973      0.984      0.728

Others models Counter Strike 2 YOLOv10m Object Detection

https://huggingface.co./ChitoParedes/cs2-yolov10m