Call function to convert data in results to :obj:`torch.Tensor`. Args: results (dict): Result dict contains the data to convert.

Call function to convert image in results to :obj:`torch.Tensor` and transpose the channel order. Args: results (dict): R

Call function to convert image in results to :obj:`torch.Tensor` and transpose the channel order. Args: results (dict): R

Call function to convert data in results to :obj:`mmcv.DataContainer`. Args: results (dict): Result dict contains the dat

Call function to transform and format common fields in results. Args: results (dict): Result dict contains the data to convert.

Call function to collect keys in results. The keys in ``meta_keys`` will be converted to :obj:mmcv.DataContainer. Args: r

Adds Conditional Batch norm to the TF Graph. Args: inputs: Tensor of inputs (e.g. images). labels: Tensor of labels - sam

Adds Batch Norm to the TF Graph. Args: inputs: Tensor of inputs (e.g. images). Returns: Output tensor.

Call function to load images into results. Args: results (dict): A result dict contains the file name of the imag

Call function to apply test time augment transforms on results. Args: results (dict): Result dict contains the data to transform.

Call function to resize images, semantic segmentation map to multiple of size divisor. Args: results (dict): Result dict

Call function to resize images, bounding boxes, masks, semantic segmentation map. Args: results (dict): Result dict from

Call function to flip bounding boxes, masks, semantic segmentation maps. Args: results (dict): Result dict from loading p

Call function to pad images, masks, semantic segmentation maps. Args: results (dict): Result dict from loading pipeline.

Call function to normalize images. Args: results (dict): Result dict from loading pipeline. Returns: dict: N

Call function to rerange images. Args: results (dict): Result dict from loading pipeline. Returns: dict: Rera

Call function to Use CLAHE method process images. Args: results (dict): Result dict from loading pipeline. Returns:

Call function to randomly crop images, semantic segmentation maps. Args: results (dict): Result dict from loading pipeline.

Call function to rotate image, semantic segmentation maps. Args: results (dict): Result dict from loading pipeline. Retu

Call function to convert RGB image to grayscale image. Args: results (dict): Result dict from loading pipeline. Returns:

Call function to process the image with gamma correction. Args: results (dict): Result dict from loading pipeline. Retur

Call function to scale the semantic segmentation map. Args: results (dict): Result dict from loading pipeline. Returns:

Call function to perform photometric distortion on images. Args: results (dict): Result dict from loading pipeline. Retu

Call function to drop some regions of image.

Call function to make a mosaic of image. Args: results (dict): Result dict. Returns: dict: Result dict with

Call functions to load image and get image meta information. Args: results (dict): Result dict from :obj:`mmseg.CustomDataset`.

Call function to load multiple types annotations. Args: results (dict): Result dict from :obj:`mmseg.CustomDataset`. Ret

Call function to apply transforms sequentially. Args: data (dict): A result dict contains the data to transform. Returns

Call function to convert data in results to :obj:`torch.Tensor`. Args: results (dict): Result dict contains the data to convert.

Call function to convert image in results to :obj:`torch.Tensor` and transpose the channel order. Args: results (dict): R

Call function to convert image in results to :obj:`torch.Tensor` and transpose the channel order. Args: results (dict): R

Call function to convert data in results to :obj:`mmcv.DataContainer`. Args: results (dict): Result dict contains the dat

Call function to transform and format common fields in results. Args: results (dict): Result dict contains the data to convert.

Call function to collect keys in results. The keys in ``meta_keys`` will be converted to :obj:mmcv.DataContainer. Args: r

Get training/test data after pipeline. Args: idx (int): Index of data. Returns: dict: Training/test data (wi

Get item from original dataset.

Get training/test data after pipeline. Args: idx (int): Index of data. Returns: dict: Training/test data (wi

Get item from original dataset.