--- language: - en - es base_model: - jameslahm/yolov10s tags: - GAMES - COUNTER STRIKE2 - CS2 - VIDEOGAMES - CS - OBJECT DETECTION - YOLO - YOLOV10 - YOLOV10S pipeline_tag: object-detection --- # Counter Strike 2 players detector #### Supported Labels ['CT', 'CT_head', 'T', 'T_head'] #### ALL my models YOLOv10 & YOLOv9 - Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s - Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c - Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m - Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b #### 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 ``` #### Others models Counter Strike 2 YOLOv10m Object Detection https://huggingface.co/ChitoParedes/cs2-yolov10m