{"id":15414256,"url":"https://github.com/jparedesds/cs2-object-dectection","last_synced_at":"2026-01-11T03:03:55.380Z","repository":{"id":256989523,"uuid":"856964354","full_name":"jparedesDS/cs2-object-dectection","owner":"jparedesDS","description":"YOLOv9 / YOLOv10 - Players Identification of CS2","archived":false,"fork":false,"pushed_at":"2024-10-01T09:10:28.000Z","size":15089,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-10-06T02:05:55.222Z","etag":null,"topics":["counter-strike","model","object-detection","opencv","pytorch","ultralytics","yolov10","yolov9"],"latest_commit_sha":null,"homepage":"https://huggingface.co/jparedesDS","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Counter Strike 2 Players Detector\n\n#### Supported Labels\n['CT', 'CT_head', 'T', 'T_head']\n\n#### MODELS YOLOv9, YOLOv10, YOLO12 for Counter Strike 2 Object Detection\n- Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c\n- Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s\n- Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m\n- Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b\n- Yolo12s: https://huggingface.co/jparedesDS/cs2_yolo12s\n\n#### ALL my models YOLO11, YOLOv10\n- Yolov10b: https://huggingface.co/jparedesDS/valorant-yolov10b\n- Yolo11m: https://huggingface.co/jparedesDS/valorant-yolo11m\n- Yolo11l: https://huggingface.co/jparedesDS/deadlock-yolo11l\n\n  \n#### How to use\n```\nfrom ultralytics import YOLO\n\n# Load a pretrained YOLO model\nmodel = YOLO(r'weights\\yolov10s_cs2.pt')\n\n# Run inference on 'image.png' with arguments\nmodel.predict(\n    'image.png',\n    save=True,\n    device=0\n    )\n```\n\n#### Labels\n![labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/KRuK-Y9uEP2Hwat5ojD1E.jpeg)\n#### Results\n![results.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/-DOb5ZmGoI_vXs7zgtFMP.png)\n#### Predict\n![train_batch0.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/Ie7m1EQosL87TbN_UoS-0.jpeg)\n![train_batch1.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/Lr3solcPWqHrdMvQ0hBX9.jpeg)\n```\nYOLOv10s summary (fused): 293 layers, 8,038,056 parameters, 0 gradients, 24.5 GFLOPs\n                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 5/5 [00:03\u003c00:00,  1.41it/s]\n                   all        160        372      0.958       0.94      0.979      0.772\n               ct_body         88        110      0.964      0.964      0.988      0.861\n               ct_head         82        104      0.946      0.847      0.953      0.634\n                t_body         70         84      0.986      0.976       0.99      0.866\n                t_head         62         74      0.938      0.973      0.984      0.728\n```\n\n#### ALL models\nhttps://huggingface.co/jparedesDS\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjparedesds%2Fcs2-object-dectection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjparedesds%2Fcs2-object-dectection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjparedesds%2Fcs2-object-dectection/lists"}