metadata
base_model:
- jparedesDS/deadlock-yolo11l
tags:
- yolo11
- deadlock
- videogames
Deadlock Players Detector
Supported Labels
['deny', 'enemy', 'hit', 'minions']
ALL my models YOLO11, YOLOv10 & YOLOv9
- Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c
- Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s
- Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m
- Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b
- Yolov10b: https://huggingface.co/jparedesDS/valorant-yolov10b
- Yolo11m: https://huggingface.co/jparedesDS/valorant-yolo11m
- Yolo11l: https://huggingface.co/jparedesDS/deadlock-yolo11l
How to use
from ultralytics import YOLO
# Load a pretrained YOLO model
model = YOLO(r'weights\yolo11l_deadlock.pt')
# Run inference on 'image.png' with arguments
model.predict(
'image.png',
save=True,
device=0
)
Confusion matrix normalized
Labels
Results
Predict
YOLO11l summary (fused): 464 layers, 25,282,396 parameters, 0 gradients, 86.6 GFLOPs
Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 8/8 [00:03<00:00, 2.37it/s]
all 551 661 0.874 0.798 0.856 0.486
deny 13 14 0.748 0.857 0.819 0.48
enemy 197 228 0.942 0.785 0.883 0.508
hit 40 53 0.861 0.704 0.787 0.409
minions 222 366 0.945 0.847 0.933 0.546