Spaces:
Sleeping
Sleeping
File size: 2,169 Bytes
4258af6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.models.yolo.detect.predict import DetectionPredictor
from ultralytics.utils import DEFAULT_CFG, LOGGER, ops
class PosePredictor(DetectionPredictor):
"""
A class extending the DetectionPredictor class for prediction based on a pose model.
Example:
```python
from ultralytics.utils import ASSETS
from ultralytics.models.yolo.pose import PosePredictor
args = dict(model="yolo11n-pose.pt", source=ASSETS)
predictor = PosePredictor(overrides=args)
predictor.predict_cli()
```
"""
def __init__(self, cfg=DEFAULT_CFG, overrides=None, _callbacks=None):
"""Initializes PosePredictor, sets task to 'pose' and logs a warning for using 'mps' as device."""
super().__init__(cfg, overrides, _callbacks)
self.args.task = "pose"
if isinstance(self.args.device, str) and self.args.device.lower() == "mps":
LOGGER.warning(
"WARNING ⚠️ Apple MPS known Pose bug. Recommend 'device=cpu' for Pose models. "
"See https://github.com/ultralytics/ultralytics/issues/4031."
)
def construct_result(self, pred, img, orig_img, img_path):
"""
Constructs the result object from the prediction.
Args:
pred (torch.Tensor): The predicted bounding boxes, scores, and keypoints.
img (torch.Tensor): The image after preprocessing.
orig_img (np.ndarray): The original image before preprocessing.
img_path (str): The path to the original image.
Returns:
(Results): The result object containing the original image, image path, class names, bounding boxes, and keypoints.
"""
result = super().construct_result(pred, img, orig_img, img_path)
pred_kpts = pred[:, 6:].view(len(pred), *self.model.kpt_shape) if len(pred) else pred[:, 6:]
pred_kpts = ops.scale_coords(img.shape[2:], pred_kpts, orig_img.shape)
result.update(keypoints=pred_kpts)
return result
|