Concatenates a list of BoxList (having the same image size) into a single BoxList Arguments: bboxes (list[BoxList])

Add a conv2d / batchnorm / leaky ReLU block. Args: in_ch (int): number of input channels of the convolution layer. out_ch (in

Efficient version of torch.cat that avoids a copy if there is only a single element in a list

Args: num_channels: conv_channels: first_time: whether the input comes directly from the efficientnet,

Update the scene manager with new sensor data and new 2D detections. Args: data: Dictionary of sensor data.

Compute the intersection over union of two set of boxes. The box order must be (xmin, ymin, xmax, ymax). Arguments: box1: (BoxList) bou

Represent as a 4x4 matrix.

Represent as a 4x4 matrix.

1x1 convolution

Get the bounding box of the object. Args: obj_name: name of the object Returns: bbox: np.ndarray, [x_

Reset the robot to the initial state and opens the gripper.

tensors can be an ImageList, a torch.Tensor or an iterable of Tensors. It can't be a numpy array. When tensors is an iterable of Tensors,

3x3 convolution with padding

5x5 convolution with padding

7x7 convolution with padding

Args: depth_img: The depth image. intrinsic: The intrinsic parameters of a pinhole camera model. extrinsi

Only keep boxes with both sides >= min_size Arguments: boxlist (Boxlist) min_size (int)

Run all_gather on arbitrary picklable data (not necessarily tensors) Args: data: any picklable object Returns: list[data]

Inputs: - input_labels: Variable long (batch, seq_len) Outputs: - output : Variable

Accumulate per image evaluation results and store the result in self.eval.

Performs all_gather operation on the provided tensors. *** Warning ***: torch.distributed.all_gather has no gradient.

Performs non-maximum suppression on a boxlist, with scores specified in a boxlist field via score_field. Arguments: boxlist(BoxL

evaluate dataset using different methods based on dataset type. Args: dataset: Dataset object predictions(list[BoxList]): each ite

Get all object names in the world.

This function recursively loads the config files and merge it into the base config.

Calculate and round number of filters based on depth multiplier.