feat: ✨ Keypoints for detectron2 added

Signed-off-by: Onuralp SEZER <[email protected]>

supervision/keypoint/core.py

@@ -414,6 +414,50 @@ def from_yolo_nas(cls, yolo_nas_results) -> KeyPoints:
  data=data,
  )
 
+ @classmethod
+ def from_detectron2(cls, detectron2_results) -> KeyPoints:
+ """
+ Create a `sv.KeyPoints` object from the
+ [Detectron2](https://github.com/facebookresearch/detectron2) inference result.
+
+ Args:
+ detectron2_results: The output of a
+ Detectron2 model containing instances with prediction data.
+
+ Returns:
+ A `sv.KeyPoints` object containing the keypoint coordinates, class IDs,
+ and class names, and confidences of each keypoint.
+
+ Example:
+ ```python
+ import cv2
+ import supervision as sv
+ from detectron2.engine import DefaultPredictor
+ from detectron2.config import get_cfg
+
+
+ image = cv2.imread(<SOURCE_IMAGE_PATH>)
+ cfg = get_cfg()
+ cfg.merge_from_file(<CONFIG_PATH>)
+ cfg.MODEL.WEIGHTS = <WEIGHTS_PATH>
+ predictor = DefaultPredictor(cfg)
+
+ result = predictor(image)
+ keypoints = sv.Keypoints.from_detectron2(result)
+ ```
+ """
+
+ return cls(
+ xy=detectron2_results["instances"].pred_keypoints.cpu().numpy()[:, :, :2],
+ confidence=detectron2_results["instances"]
+ .pred_keypoints.cpu()
+ .numpy()[:, :, 2:],
+ class_id=detectron2_results["instances"]
+ .pred_classes.cpu()
+ .numpy()
+ .astype(int),
+ )
+
  def __getitem__(
  self, index: Union[int, slice, List[int], np.ndarray, str]
  ) -> Union[KeyPoints, List, np.ndarray, None]: