| 106 | |
| 107 | |
| 108 | def get_pulsar_camera_params( |
| 109 | R: torch.Tensor, |
| 110 | tvec: torch.Tensor, |
| 111 | camera_matrix: torch.Tensor, |
| 112 | image_size: torch.Tensor, |
| 113 | znear: float = 0.1, |
| 114 | ) -> torch.Tensor: |
| 115 | assert len(camera_matrix.size()) == 3, "This function requires batched inputs!" |
| 116 | assert len(R.size()) == 3, "This function requires batched inputs!" |
| 117 | assert len(tvec.size()) in (2, 3), "This function reuqires batched inputs!" |
| 118 | |
| 119 | # Validate parameters. |
| 120 | image_size_wh = image_size.to(R).flip(dims=(1,)) |
| 121 | assert torch.all( |
| 122 | image_size_wh > 0 |
| 123 | ), "height and width must be positive but min is: %s" % ( |
| 124 | str(image_size_wh.min().item()) |
| 125 | ) |
| 126 | assert ( |
| 127 | camera_matrix.size(1) == 3 and camera_matrix.size(2) == 3 |
| 128 | ), "Incorrect camera matrix shape: expected 3x3 but got %dx%d" % ( |
| 129 | camera_matrix.size(1), |
| 130 | camera_matrix.size(2), |
| 131 | ) |
| 132 | assert ( |
| 133 | R.size(1) == 3 and R.size(2) == 3 |
| 134 | ), "Incorrect R shape: expected 3x3 but got %dx%d" % ( |
| 135 | R.size(1), |
| 136 | R.size(2), |
| 137 | ) |
| 138 | if len(tvec.size()) == 2: |
| 139 | tvec = tvec.unsqueeze(2) |
| 140 | assert ( |
| 141 | tvec.size(1) == 3 and tvec.size(2) == 1 |
| 142 | ), "Incorrect tvec shape: expected 3x1 but got %dx%d" % ( |
| 143 | tvec.size(1), |
| 144 | tvec.size(2), |
| 145 | ) |
| 146 | # Check batch size. |
| 147 | batch_size = camera_matrix.size(0) |
| 148 | assert R.size(0) == batch_size, "Expected R to have batch size %d. Has size %d." % ( |
| 149 | batch_size, |
| 150 | R.size(0), |
| 151 | ) |
| 152 | assert ( |
| 153 | tvec.size(0) == batch_size |
| 154 | ), "Expected tvec to have batch size %d. Has size %d." % ( |
| 155 | batch_size, |
| 156 | tvec.size(0), |
| 157 | ) |
| 158 | # Check image sizes. |
| 159 | image_w = image_size_wh[0, 0] |
| 160 | image_h = image_size_wh[0, 1] |
| 161 | assert torch.all( |
| 162 | image_size_wh[:, 0] == image_w |
| 163 | ), "All images in a batch must have the same width!" |
| 164 | assert torch.all( |
| 165 | image_size_wh[:, 1] == image_h |