Resize images with ``results['scale']``.

Resize semantic segmentation map with ``results['scale']``.

Saves module state to `destination` dictionary. This method is modified from :meth:`torch.nn.Module._save_to_state_dict`. Args: modu

Saves module state to `destination` dictionary. This method is modified from :meth:`torch.nn.Module._save_to_state_dict`. Args: modu

Substitute variable strings to their actual values.

Convert image based absolute point coordinates to image based relative coordinates for sampling. Args: abs_img_points (Tensor): Image

Add all parameters of module to the params list. The parameters of the given module will be added to the list of param groups, with s

Called after every training epoch to evaluate the results.

Called after every training iter to evaluate the results.

Placeholder for augmentation test.

Scaling bboxes w.r.t the box center. Args: bboxes (ndarray): Shape(..., 4). scale (float): Scaling factor. clip_shape (tu

initialize conv/fc bias value according to a given probability value.

Given an input and a flow-field grid, computes the output using input values and pixel locations from grid. Supported only bilinear interpolation

Brightness distortion.

Builder for attention.

Builder for feed-forward network (FFN).

Build padding layer. Args: cfg (None or dict): The padding layer config, which should contain: - type (str): Layer type.

Build pixel sampler for segmentation map.

Build plugin layer. Args: cfg (None or dict): cfg should contain: type (str): identify plugin layer type. layer a

Build segmentor.

Builder for transformer layer.

Build upsample layer. Args: cfg (dict): The upsample layer config, which should contain: - type (str): Layer type.

Calculating square distance between a and b. Args: point_feat_a (Tensor): (B, N, C) Feature vector of each point. point_feat_b (T

CAM feature classification.

Convert camel case word into snack case. Modified from `inflection lib <https://inflection.readthedocs.io/en/latest/#inflection.under

Add check points in a single line. This method is suitable for running a task on a list of items. A timer will be registered when the method

Puts each data field into a tensor/DataContainer with outer dimension batch size. Extend default_collate to add support for :type:`~mmcv.

Collect the information of the running environments.

Collect results with CPU.

Collect results under cpu mode. On cpu mode, this function will save the results on different gpus to ``tmpdir`` and collect them by the rank

Collect results with GPU.

Collect results under gpu mode. On gpu mode, this function will encode results to gpu tensors and use gpu communication for results collectio

3x3 convolution with padding.

Get current momentums. Returns: list[float] | dict[str, list[float]]: Current momentums of all param groups. If t

Dequantize an array. Args: arr (ndarray): Input array. min_val (scalar): Minimum value to be clipped. max_val (scalar): M

Recover from quantized flow. Args: dx (ndarray): Quantized dx. dy (ndarray): Quantized dy. max_val (float): Maximum value

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). We follow the implementation https://github.com/

Placeholder for extract features from images.

calcuate the f-score value. Args: precision (float | torch.Tensor): The precision value. recall (float | torch.Tensor): The recal

Convert flow map to RGB image. Args: flow (ndarray): Array of optical flow. color_wheel (ndarray or None): Color wheel used to ma

Read an optical flow map. Args: flow_or_path (ndarray or str): A flow map or filepath. quantize (bool): whether to read quantized

Format the results into dir (standard format for Cityscapes evaluation). Args: results (list): Testing results of the dat

Forward function.

Forward function.

Generate config from config str. Args: cfg_str (str): Config str. file_format (str): Config file format corresponding

Fused bias leaky ReLU function. This function is introduced in the StyleGAN2: http://arxiv.org/abs/1912.04958 The bias term comes from t

Generate regular square grid of points in [0, 1] x [0, 1] coordinate space. Args: num_grid (int): The number of grids to sample, one

Get annotation by index. Args: idx (int): Index of data. Returns: dict: Annotation info of specified index.

Get class names of current dataset. Args: classes (Sequence[str] | str | None): If classes is None, use default C

Get the git hash of the current repo. Args: fallback (str, optional): The fallback string when git hash is unavailable. Defau

Get ground truth segmentation maps for evaluation.

Get class palette (RGB) of a dataset.