Edit model card

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

Counter Strike 2 players detector

Supported Labels

[ "none", "ct_body", "ct_head", "t_body", "t_head" ]

models

YOLOv10b

How to use

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolov10b_cs2.pt')

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

Labels

labels.jpg

Results

results.png

Predict

train_batch0.jpg

YOLOv10b summary (fused): 383 layers, 20,418,862 parameters, 0 gradients, 98.0 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 3/3 [00:02<00:00,  1.44it/s]
                   all         90        215      0.908      0.757       0.85      0.635
               ct_body         41         45      0.914      0.911      0.953      0.819
               ct_head         43         47      0.909      0.639      0.735      0.465
                t_body         54         60      0.932      0.921      0.964      0.781
                t_head         56         63      0.877      0.556      0.748      0.476

others models YOLOv10s

https://huggingface.co/ChitoParedes/cs2-yolov10s

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model's library. Check the docs .

Model tree for jparedesDS/cs2-yolov10b

Finetuned
(1)
this model

Collection including jparedesDS/cs2-yolov10b