jparedesDS/ow2-yolo11m

Overwatch 2 Players Detector

Supported Labels

['Head']

ALL my models YOLO11, YOLOv10 & YOLOv9

• YOLO11l: https://huggingface.co/jparedesDS/fluorescent-penetrant-inspection
• YOLO11x: https://huggingface.co/jparedesDS/welding-defects-detection
• 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
• YOLO11l: https://huggingface.co/jparedesDS/ow2-yolo11m

How to use

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\ow2-yolo11m.pt')

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

Confusion matrix normalized

Labels

Results

Predict

YOLO11m summary (fused): 303 layers, 20,030,803 parameters, 0 gradients, 67.6 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 4/4 [00:01<00:00,  2.69it/s]
                   all        273        133      0.742      0.563       0.66      0.317

Others models...

https://huggingface.co/jparedesDS/