COCO label names and correspondence between the model's class index and COCO class index. Returns: coco_label_names (tuple of str) :

Equivalent to nn.functional.interpolate, but with support for empty batch sizes. This will eventually be supported natively by PyTorch, and t

:param boxes1: boxes1和boxes2的shape可以不相同，但是需要满足广播机制，且需要是Tensor :param boxes2: 且需要保证最后一维为坐标维，以及坐标的存储结构为(x, y, w, h) :return: 返回boxes1和boxes

:param boxes1: boxes1和boxes2的shape可以不相同，但是需要满足广播机制，且需要是Tensor :param boxes2: 且需要保证最后一维为坐标维，以及坐标的存储结构为(xmin, ymin, xmax, ymax) :return: 返回

:param bboxes: 假设有N个bbox的score大于score_threshold，那么bboxes的shape为(N, 6)，存储格式为(xmin, ymin, xmax, ymax, score, class) 其中(xmin, ymin, xmax, ym

Performs Rotate-Non-Maximum Suppression (RNMS) on inference results； @param prediction: size=(batch_size, num, [xywh,score,num_classe

Parse a PASCAL VOC xml file

perform random distortion in the HSV color space. Args: img (numpy.ndarray): input image whose shape is :math:`(H, W, C)`.

Args: input_dict (dict): all the values will be reduced average (bool): whether to do average or sum Reduce the values in the

r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained

r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained

r"""ResNet-18 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

r"""ResNet-50 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrained (

r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_. Arg

r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_. Args

Helper function to synchronize (barrier) among all processes when using distributed training

Warning: does not synchronize the deque!

Decorator to make all processes in distributed training wait for each local_master to do something.