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import torch
import numpy as np
from detectron2.structures import Boxes
def cube_to_box(cube,K):
'''
Converts a Cube to a Box.
Args:
cube: A Cube.
K: The 3D camera matrix of the box.
Returns:
A Box.
'''
bube_corners = cube.get_bube_corners(K)
min_x = torch.min(bube_corners[:,0])
max_x = torch.max(bube_corners[:,0])
min_y = torch.min(bube_corners[:,1])
max_y = torch.max(bube_corners[:,1])
return Boxes(torch.tensor([[min_x, min_y, max_x, max_y]], device=cube.tensor.device))
def cubes_to_box(cubes, K, im_shape):
'''
Converts a Cubes to a Boxes.
Args:
cubes: A Cubes.
K: The 3D camera matrix of the box.
im_shape: The shape of the image (width, height).
Returns:
A Box.
'''
bube_corners = cubes.get_bube_corners(K, im_shape)
min_x, _ = torch.min(bube_corners[:, :, :, 0], 2)
max_x, _ = torch.max(bube_corners[:, :, :, 0], 2)
min_y, _ = torch.min(bube_corners[:, :, :, 1], 2)
max_y, _ = torch.max(bube_corners[:, :, :, 1], 2)
values = torch.stack((min_x, min_y, max_x, max_y),dim=2)
box_list = []
for i in range(cubes.num_instances):
box_list.append(Boxes(values[i]))
return box_list
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