| # Dynamic SpatialVID Inference |
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| Wrappers for checkpoints trained on the dynamic SpatialVID motion-filtered pool. They call `inference/unified_inference.py` and mirror the six public dynamic rows: |
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| | Script | `--memory_type` | Training recipe | |
| | --- | --- | --- | |
| | `run_infer_dyn_ctx1.sh` | `context_k1` | `train/dynamic_spatialvid/run_dyn_ctx1.sh` | |
| | `run_infer_dyn_ctx5.sh` | `context_k5` | `train/dynamic_spatialvid/run_dyn_ctx5.sh` | |
| | `run_infer_dyn_ctx20.sh` | `context_k20` | `train/dynamic_spatialvid/run_dyn_ctx20.sh` | |
| | `run_infer_dyn_spatial_mem.sh` | `spatial_mem` | `train/dynamic_spatialvid/run_dyn_spatial_mem.sh` | |
| | `run_infer_dyn_block_wise_ssm.sh` | `block_wise_ssm` | `train/dynamic_spatialvid/run_dyn_block_wise_ssm.sh` | |
| | `run_infer_dyn_videossm_hybrid.sh` | `videossm_hybrid` | `train/dynamic_spatialvid/run_dyn_videossm_hybrid.sh` | |
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| ```bash |
| export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B |
| export CKPT=/path/to/retrained_dynamic_spatial_mem/epoch-0.safetensors |
| PROMPT="A dynamic outdoor scene with a smooth camera move" \ |
| bash inference/dynamic_spatialvid/run_infer_dyn_spatial_mem.sh |
| ``` |
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| To run all six rows: |
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| ```bash |
| CKPT_DIR=./ckpts/dynamic_spatialvid bash inference/dynamic_spatialvid/run_infer_all_dyn.sh |
| ``` |
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| ## Demo Selection |
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| Dynamic demos should be selected from training scenes by random replay, then manually picked: |
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| 1. Sample candidate rows from `metadata_train.csv` or a small public subset such as `metadata_train_sample.csv`. |
| 2. Replay the same scene/prompt/action with all six dynamic checkpoints. |
| 3. Pick representative successes for the public preview grid. |
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| Evaluation for the dynamic benchmark is intentionally TODO for now; only training and inference wrappers are public. |
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