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ultralytics 8.3.67 NMS Export for Detect, Segment, Pose and OBB YOLO models (#18484)

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Signed-off-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
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Mohammed Yasin 2025-01-24 18:00:36 +08:00 • committed by GitHub
parent 0e48a00303
commit 9181ff62f5
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17 changed files with 320 additions and 208 deletions
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37
ultralytics/models/yolo/obb/predict.py
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@ -27,27 +27,20 @@ class OBBPredictor(DetectionPredictor):
super().__init__(cfg, overrides, _callbacks)
self.args.task = "obb"
def postprocess(self, preds, img, orig_imgs):
"""Post-processes predictions and returns a list of Results objects."""
preds = ops.non_max_suppression(
preds,
self.args.conf,
self.args.iou,
agnostic=self.args.agnostic_nms,
max_det=self.args.max_det,
nc=len(self.model.names),
classes=self.args.classes,
rotated=True,
)
def construct_result(self, pred, img, orig_img, img_path):
"""
Constructs the result object from the prediction.
if not isinstance(orig_imgs, list): # input images are a torch.Tensor, not a list
orig_imgs = ops.convert_torch2numpy_batch(orig_imgs)
Args:
pred (torch.Tensor): The predicted bounding boxes, scores, and rotation angles.
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.
results = []
for pred, orig_img, img_path in zip(preds, orig_imgs, self.batch[0]):
rboxes = ops.regularize_rboxes(torch.cat([pred[:, :4], pred[:, -1:]], dim=-1))
rboxes[:, :4] = ops.scale_boxes(img.shape[2:], rboxes[:, :4], orig_img.shape, xywh=True)
# xywh, r, conf, cls
obb = torch.cat([rboxes, pred[:, 4:6]], dim=-1)
results.append(Results(orig_img, path=img_path, names=self.model.names, obb=obb))
return results
Returns:
(Results): The result object containing the original image, image path, class names, and oriented bounding boxes.
"""
rboxes = ops.regularize_rboxes(torch.cat([pred[:, :4], pred[:, -1:]], dim=-1))
rboxes[:, :4] = ops.scale_boxes(img.shape[2:], rboxes[:, :4], orig_img.shape, xywh=True)
obb = torch.cat([rboxes, pred[:, 4:6]], dim=-1)
return Results(orig_img, path=img_path, names=self.model.names, obb=obb)