| # Visualization Suite (no code changes) | |
| This folder adds **standalone** visualization scripts. It does **not** modify any existing training/inference code. | |
| ## Quick start | |
| 1. Prepare prediction folders for each method (ours + baselines). | |
| Supported formats (per-case): | |
| - `*_label.nii.gz` (label map, values {0,1,2,4}) | |
| - `*_regions_prob.nii.gz` (probabilities for WT/TC/ET) | |
| - `*_regions_bin.nii.gz` (binary WT/TC/ET) | |
| - `{case_id}.nii.gz` (SegMamba 3-channel) | |
| 2. Copy and edit the config: | |
| ```bash | |
| cp visualizations/vis_config_example.yaml visualizations/vis_config.yaml | |
| ``` | |
| 3. Run (full suite): | |
| ```bash | |
| python visualizations/vis_suite.py --config visualizations/vis_config.yaml --checkpoint /path/to/ckpt.pt --run all | |
| ``` | |
| 4. Run a subset (comma-separated): | |
| ```bash | |
| python visualizations/vis_suite.py --config visualizations/vis_config.yaml --checkpoint /path/to/ckpt.pt --run qualitative,et_absent,boundary | |
| ``` | |
| ## Notes | |
| - Model-dependent visualizations (`et_absent`, `moe`, `dual_domain`, `ampmix`) require `--checkpoint`. | |
| - Aux outputs (pi_ET, MoE routing, spectral outputs) are cached to `predictions.aux_dir` when provided. | |
| - Output figures are saved to `visualization.output_dir` (default: `visualizations/outputs`). | |
| - If `matplotlib` is missing, install it in your environment. | |