Prediction each pixel.

Encode an image into a vector descriptor containing both global and local features. Args: image (Tensor): Tensor of shap

Encode a text input into a vector descriptor. Args: text (Tensor): Tensor of shape `(batch_size, seq_len)` containing to

Extract features from images.

Extract features from images.

Extract features from images.

Estimate disparity between pair of frames

Forward function for `FFN`. The function would add x to the output tensor if residue is None.

Placeholder of forward function.

Placeholder of forward function.

Forward for head part which is called after every decoder layer. Args: decoder_out (Tensor): in shape (num_queries, batch_size, c

Args: imgs (List[Tensor]): the outer list indicates test-time augmentations and inner Tensor should have a shape

Args: imgs (List[Tensor]): the outer list indicates test-time augmentations and inner Tensor should have a shape

Forward function for training. Args: img (Tensor): Input images. img_metas (list[dict]): List of image info dict wher

this will perform the index select, cat the tensors, and provide the attn_bias from cache

Returns: The rank of the current process within the global process group.

Returns: The number of processes in the process group

Compute classification and mask targets for all images for a decoder layer. Args: cls_scores_list (list[Tensor]): Mask sc

Inverse function of sigmoid. Args: x (Tensor): The tensor to do the inverse. eps (float): EPS avoid numerical

Apply function to a list of arguments. Note: This function applies the ``func`` to multiple inputs and map the multiple outputs o

@img: (B,C,H,W) in range 0-255, RGB order

Sample positive and negative bboxes. This is a simple implementation of bbox sampling given candidates, assigning results and ground

Generate grid Points of a single level. Note: This function is usually called by method ``self.grid_priors``. Args:

Init. Args: features (int): number of features

Run forward function and calculate loss for auxiliary head in training.

Args: cls_pred (Tensor): The prediction with shape (num_query, 1, *) or (num_query, *). gt_labels (Te

Configure a logger. Adapted from Detectron2. Args: name: The name of the logger to configure. level: The logging level

Run forward function and calculate loss for decode head in inference.

Run forward function and calculate loss for decode head in inference.

Run forward function and calculate loss for decode head in inference.

Run forward function and calculate loss for decode head in training.

Run forward function and calculate loss for decode head in training.

Run forward function and calculate loss for decode head in training.

Expand onehot labels to match the size of prediction.

Forward function for feature maps before classifying each pixel with ``self.cls_seg`` fc. Args: inputs (list[Tensor]): Lis

Forward function for feature maps before classifying each pixel with ``self.cls_seg`` fc. Args: inputs (list[Tensor]): Li

Forward function for feature maps before classifying each pixel with ``self.cls_seg`` fc. Args: inputs (list[Tensor]): Lis

Generate the indices of a random permutation.

Initialize ``auxiliary_head``

Initialize ``decode_head``

Initialize ``decode_head``