https://github.com/jparedesds/cs2-object-dectection

YOLOv9 / YOLOv10 - Players Identification of CS2
https://github.com/jparedesds/cs2-object-dectection

counter-strike model object-detection opencv pytorch ultralytics yolov10 yolov9

Last synced: 7 days ago
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YOLOv9 / YOLOv10 - Players Identification of CS2

• Host: GitHub
• URL: https://github.com/jparedesds/cs2-object-dectection
• Owner: jparedesDS
• Created: 2024-09-13T14:42:44.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-10-01T09:10:28.000Z (about 2 months ago)
• Last Synced: 2024-10-06T02:05:55.222Z (about 1 month ago)
• Topics: counter-strike, model, object-detection, opencv, pytorch, ultralytics, yolov10, yolov9
• Language: Jupyter Notebook
• Homepage: https://huggingface.co/jparedesDS
• Size: 14.4 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Counter Strike 2 Players Detector

#### Supported Labels

['CT', 'CT_head', 'T', 'T_head']

#### MODELS YOLOv9, YOLOv10 for Counter Strike 2 Object 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

#### ALL my models YOLO11, YOLOv10

- 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\yolov10s_cs2.pt')

# Run inference on 'image.png' with arguments

model.predict(

    'image.png',

    save=True,

    device=0

    )

```

#### Labels

![labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/KRuK-Y9uEP2Hwat5ojD1E.jpeg)

#### Results

![results.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/-DOb5ZmGoI_vXs7zgtFMP.png)

#### Predict

![train_batch0.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/Ie7m1EQosL87TbN_UoS-0.jpeg)

![train_batch1.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/Lr3solcPWqHrdMvQ0hBX9.jpeg)

```

YOLOv10s summary (fused): 293 layers, 8,038,056 parameters, 0 gradients, 24.5 GFLOPs

                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 5/5 [00:03<00:00,  1.41it/s]

                   all        160        372      0.958       0.94      0.979      0.772

               ct_body         88        110      0.964      0.964      0.988      0.861

               ct_head         82        104      0.946      0.847      0.953      0.634

                t_body         70         84      0.986      0.976       0.99      0.866

                t_head         62         74      0.938      0.973      0.984      0.728

```

#### ALL models

https://huggingface.co/jparedesDS