Implements DeepLabV3 model from `"Rethinking Atrous Convolution for Semantic Image Segmentation" <https://arxiv.org/abs/1706.05587>`_.

Module wrapper that returns intermediate layers from a model It has a strong assumption that the modules have been registered into the m

Apply a user-defined lambda as a transform. Args: lambd (function): Lambda/function to be used for transform.

Cityscapes <http://www.cityscapes-dataset.com/> Dataset. **Parameters:** - **root** (string): Root directory of dataset where directo

`Pascal VOC <http://host.robots.ox.ac.uk/pascal/VOC/>`_ Segmentation Dataset. Args: root (string): Root directory of the VOC Dataset.

Visualizer

Xception optimized for the ImageNet dataset, as specified in https://arxiv.org/pdf/1610.02357.pdf

Atrous Separable Convolution

Composes several transforms together. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example:

Stream Metrics for Semantic Segmentation Task

Computes average values

Crops the given PIL Image at the center. Args: size (sequence or int): Desired output size of the crop. If size is an int inst

Randomly change the brightness, contrast and saturation of an image. Args: brightness (float or tuple of float (min, max)): How much to ji

Composes several transforms together. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example:

Normalize a tensor image with mean and standard deviation. Given mean: ``(M1,...,Mn)`` and std: ``(S1,..,Sn)`` for ``n`` channels, this transform

Crop the given PIL Image at a random location. Args: size (sequence or int): Desired output size of the crop. If size is an in

Horizontally flip the given PIL Image randomly with a given probability. Args: p (float): probability of the image being flipped. Default

Rotate the image by angle. Args: degrees (sequence or float or int): Range of degrees to select from. If degrees is a number i

Vertically flip the given PIL Image randomly with a given probability. Args: p (float): probability of the image being flipped. Default va

Resize the input PIL Image to the given size. Args: size (sequence or int): Desired output size. If size is a sequence like (h

Resize the input PIL Image to the given scale. Args: Scale (sequence or int): scale factors interpolation (int, optional): Desired

Convert a ``PIL Image`` or ``numpy.ndarray`` to tensor. Converts a PIL Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.Flo