(self, lrm_generator_input)
| 167 | return frames |
| 168 | |
| 169 | def forward(self, lrm_generator_input): |
| 170 | images = lrm_generator_input['images'] |
| 171 | cameras = lrm_generator_input['cameras'] |
| 172 | render_cameras = lrm_generator_input['render_cameras'] |
| 173 | render_size = lrm_generator_input['render_size'] |
| 174 | crop_params = lrm_generator_input['crop_params'] |
| 175 | |
| 176 | out = self.forward_lrm_generator( |
| 177 | images, |
| 178 | cameras, |
| 179 | render_cameras, |
| 180 | render_size=render_size, |
| 181 | crop_params=crop_params, |
| 182 | chunk_size=1, |
| 183 | ) |
| 184 | render_images = torch.clamp(out['images_rgb'], 0.0, 1.0) |
| 185 | render_depths = out['images_depth'] |
| 186 | render_alphas = torch.clamp(out['images_weight'], 0.0, 1.0) |
| 187 | |
| 188 | out = { |
| 189 | 'render_images': render_images, |
| 190 | 'render_depths': render_depths, |
| 191 | 'render_alphas': render_alphas, |
| 192 | } |
| 193 | return out |
| 194 | |
| 195 | def training_step(self, batch, batch_idx): |
| 196 | lrm_generator_input, render_gt = self.prepare_batch_data(batch) |
no test coverage detected