HongChuang/ultralytics-ascend
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Resolve warnings (#19073)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2025-02-05 21:27:38 +09:00 • committed by GitHub
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2 changed files with 2 additions and 8 deletions
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4
ultralytics/engine/exporter.py
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@ -1544,10 +1544,10 @@ class NMSModel(torch.nn.Module):
Performs inference with NMS post-processing. Supports Detect, Segment, OBB and Pose.
Args:
x (torch.tensor): The preprocessed tensor with shape (N, 3, H, W).
x (torch.Tensor): The preprocessed tensor with shape (N, 3, H, W).
Returns:
out (torch.tensor): The post-processed results with shape (N, max_det, 4 + 2 + extra_shape).
out (torch.Tensor): The post-processed results with shape (N, max_det, 4 + 2 + extra_shape).
"""
from functools import partial

6
ultralytics/nn/tasks.py
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@ -484,12 +484,6 @@ class RTDETRDetectionModel(DetectionModel):
the training and inference processes. RTDETR is an object detection and tracking model that extends from the
DetectionModel base class.
Attributes:
cfg (str): The configuration file path or preset string. Default is 'rtdetr-l.yaml'.
ch (int): Number of input channels. Default is 3 (RGB).
nc (int, optional): Number of classes for object detection. Default is None.
verbose (bool): Specifies if summary statistics are shown during initialization. Default is True.
Methods:
init_criterion: Initializes the criterion used for loss calculation.
loss: Computes and returns the loss during training.