jparedesDS
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Browse files![results.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/k7lUu5uaNXISLyGfLkOdX.png)
![val_batch2_labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/_ku6Baq6CrSkE7ap4zQbn.jpeg)
![labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/okW-nqDnryqccYbsDt-ra.jpeg)
![val_batch1_labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/EK7SfvdOdUAY8d20IXzqI.jpeg)
![confusion_matrix_normalized.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/tE3CoiaB8ODKdQs_gTWTp.png)
README.md
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---
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tags:
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- yolo11
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- valorant
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- object
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- detection
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---
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# Valorant Players Detector
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#### Supported Labels
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['Body', 'Head']
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#### ALL my models YOLOv10 & YOLOv9
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- Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c
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- Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s
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- Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m
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- Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b
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- Yolov10b: https://huggingface.co/jparedesDS/valorant-yolov10b
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#### How to use
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```
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from ultralytics import YOLO
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# Load a pretrained YOLO model
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model = YOLO(r'weights\yolov10b_vlr.pt')
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# Run inference on 'image.png' with arguments
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model.predict(
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'image.png',
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save=True,
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device=0
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)
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```
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#### Confusion matrix normalized
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![confusion_matrix_normalized.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/tE3CoiaB8ODKdQs_gTWTp.png)
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#### Labels
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![labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/okW-nqDnryqccYbsDt-ra.jpeg)
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#### Results
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![results.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/k7lUu5uaNXISLyGfLkOdX.png)
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#### Predict
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![val_batch2_labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/_ku6Baq6CrSkE7ap4zQbn.jpeg)
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![val_batch1_labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/EK7SfvdOdUAY8d20IXzqI.jpeg)
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```
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YOLO11m summary (fused): 303 layers, 20,031,574 parameters, 0 gradients, 67.7 GFLOPs
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Class Images Instances Box(P R mAP50 mAP50-95): 100%|ββββββββββ| 11/11 [00:06<00:00, 1.71it/s]
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all 999 2016 0.963 0.898 0.931 0.655
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Body 966 1029 0.971 0.935 0.958 0.791
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Head 936 987 0.955 0.862 0.904 0.519
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```
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#### Others models Counter Strike 2 YOLOv10m Object Detection
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https://huggingface.co/jparedesDS/valorant-yolov10b
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