Yolo11n Basketball Court Keypoints
Fine-tuned yolo11n-pose.pt on koppolusameer/basketball-keypoint-detection-yolov8 (48-slot court skeleton) to detect court landmarks in broadcast frames.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 7,57 MB
- Versión
- vRevision 6cb8992
- Actualizado
- 10 oct 2026
- Descargas
- 126
- Fuente
- Hugging Face
Descripción de la fuente
YOLO11n basketball court keypoint detector
Fine-tuned yolo11n-pose.pt on koppolusameer/basketball-keypoint-detection-yolov8
(48-slot court skeleton) to detect court landmarks in broadcast frames.
Outputs keypoints in PIXEL coordinates. Converting to court coordinates (homography) is a separate downstream step requiring an index->court-location map.
Load & run
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
weights = hf_hub_download("koppolusameer/yolo11n-basketball-court-keypoints", "best.pt")
model = YOLO(weights)
r = model("frame.jpg")[0]
kxy = r.keypoints.xy[0].cpu().numpy() # (48,2) pixel coords
kconf = r.keypoints.conf[0].cpu().numpy() # (48,) confidence
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 10 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- license: agpl-3.0 tags: [ultralytics, yolo11, pose, keypoint-detection, basketball, court-registration] library_name: ultralytics --- # YOLO11n basketball court keypoint detector Fine-tuned `yolo11n-pose.pt` on `koppolusameer/basketball-keypoint-detection-yolov8` (48-slot court skeleton) to detect court landmarks in broadcast frames. Outputs keypoints in PIXEL coordinates. Converting to court coordinates (homography) is a separate downstream step requiring an index->court-location map. ## Load & run ```python from ultralytics import YOLO from huggingface_hub import hf_hub_download weights = hf_hub_download("koppolusameer/yolo11n-basketball-court-keypoints", "best.pt") model = YOLO(weights) r = model("frame.jpg")[0] kxy = r.keypoints.xy[0].cpu().numpy() # (48,2) pixel coords kconf = r.keypoints.conf[0].cpu().numpy() # (48,) confidence ```
Source context: 126 downloads · 0 likes · Pipeline keypoint-detection · Library ultralytics · Repo koppolusameer/yolo11n-basketball-court-keypoints
Source context: 70 downloads · 0 likes · Pipeline keypoint-detection · Library ultralytics · Repo koppolusameer/yolo11n-basketball-court-keypoints
