Inputs: x - (N, F) y - (N, F) Output: output - (N, 1) dot-product output

Each element of x and y are (N, F, H, W) and (1, F, H, W) tensors. The required output is a (N, 1) matrix of similarities.

See :class:`ROIHeads.forward`.

Inputs: x - (N, F) y - (N, F) Output: output - (N, 1) dot-product output

Each element of x and y are (N, F, H, W) and (1, F, H, W) tensors. The required output is a (N, 1) matrix of similarities.

See :class:`ROIHeads.forward`.

Args: batched_inputs: a list, batched outputs of :class:`DatasetMapper` . Each item in the list contains the inpu

Apply diagonal covaraiance normally-distributed noise to the N,D array x. Parameters: ----------- x : array (N,D) array of

Get a set of frames from a particular sequence args: seq_id - index of sequence frame_ids - a list of frame nu

Get a image args: image_id - index of image anno(None) - The annotation for the sequence (see get_sequence_info

Returns information about a particular image, args: seq_id - index of the image returns: Dict

Get the instance associated with a given instance id. Args: instance_id (str): the instance id (number) Returns

Gets the instance ids from the instances dictionary. Args: None Returns: keys (list): a list of key

Name of the dataset returns: string - Name of the dataset

Name of the dataset returns: string - Name of the dataset

The 1st element of the inp_list is about the template, the 2nd (the last) element is about the search region

Returns information about a particular sequences, args: seq_id - index of the sequence returns: Dict

Overload this in your dataset. Should return the list of sequences in the dataset.

Returns the list of templates. Args: None Returns: self.templates (list): the list of TemplateImage

:param boxes1: (N, 4) (x1,y1,x2,y2) :param boxes2: (N, 4) (x1,y1,x2,y2) :return:

Check if there exist a parameter with the given name.