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jparedesDS
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valorant-yolov10b

Object Detection
YOLOv10
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valorant
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Valorant Players Detector

Supported Labels

['Body', 'Head']

ALL my models YOLOv10 & YOLOv9

How to use 

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolov10b_vlr.pt')

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

Confusion matrix normalized

confusion_matrix_normalized.png

Labels

labels.jpg

Results

results.png

Predict

train_batch34921.jpg val_batch0_pred.jpg

YOLOv10b summary (fused): 383 layers, 20,414,236 parameters, 0 gradients, 97.9 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 36/36 [00:06<00:00,  5.30it/s]
                   all        999       2016      0.959      0.886      0.925      0.631
                  Body        966       1029      0.969      0.914      0.955       0.76
                  Head        936        987      0.948      0.857      0.896      0.503

Others models Counter Strike 2 YOLOv10m Object Detection

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

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