| """TIPSv2 DPT head configuration.""" | |
| from transformers import PretrainedConfig | |
| class TIPSv2DPTConfig(PretrainedConfig): | |
| """Configuration for TIPSv2 DPT dense prediction heads.""" | |
| model_type = "tipsv2_dpt" | |
| def __init__( | |
| self, | |
| backbone_repo="google/tipsv2-l14", | |
| embed_dim=1024, | |
| channels=256, | |
| post_process_channels=(128, 256, 512, 1024), | |
| block_indices=(5, 11, 17, 23), | |
| readout_type="project", | |
| num_depth_bins=256, | |
| min_depth=1e-3, | |
| max_depth=10.0, | |
| num_seg_classes=150, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) | |
| self.backbone_repo = backbone_repo | |
| self.embed_dim = embed_dim | |
| self.channels = channels | |
| self.post_process_channels = list(post_process_channels) | |
| self.block_indices = list(block_indices) | |
| self.readout_type = readout_type | |
| self.num_depth_bins = num_depth_bins | |
| self.min_depth = min_depth | |
| self.max_depth = max_depth | |
| self.num_seg_classes = num_seg_classes | |