2d3ec435b0d22e8abb3c37d80bdaff248d98d5b4,test/test_functional.py,,test_convert_points_from_homogeneous,#Any#Any#,12

Before Change

    // generate input data
    points_h = torch.rand(2, 3)
    if expand:
        points_h = torch.rand(batch_size, 2, 3)
    points_h[..., -1] = 1.0

    // to euclidean
    points = tgm.convert_points_from_homogeneous(points_h)

After Change

        num_points = 2
        num_dims = 2
        eye_size = 3  // identity 3x3
        points_src = torch.rand(batch_size, 2, num_dims)
        points_src = utils.tensor_to_gradcheck_var(points_src)  // to var
        dst_homo_src = utils.create_random_homography(batch_size, eye_size)
        dst_homo_src = utils.tensor_to_gradcheck_var(dst_homo_src)  // to var

Instances